multiresolution in h2(t) generated by a special malmquist ... · university of p ecs, hungary 1...

77
Summary Motivation Totik’s recovery theorem Recovery The continuous voice transform Reconstruction algorithm References END Numerical Harmonic Analysis Group Multiresolution in H 2 (T ) generated by a special Malmquist-Takenaka System Margit Pap, Marie Curie Fellow, NuHAG Univ. Vienna University of P´ ecs, Hungary 1 [email protected], [email protected] July 10, 2011 1 University of P´ ecs, Hungary, NuHAG Margit Pap, Marie Curie Fellow, NuHAG Univ. ViennaUniversity of P´ Multiresolution in H 2 (T ) generated by a special Malmquist-Ta

Upload: others

Post on 22-Jan-2021

1 views

Category:

Documents


0 download

TRANSCRIPT

Page 1: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Numerical Harmonic Analysis Group

Multiresolution in H2(T ) generated by a specialMalmquist-Takenaka System

Margit Pap,Marie Curie Fellow, NuHAG Univ. Vienna

University of Pecs, Hungary 1

[email protected], [email protected]

July 10, 2011

1University of Pecs, Hungary, NuHAGMargit Pap, Marie Curie Fellow, NuHAG Univ. ViennaUniversity of Pecs, Hungary [email protected], [email protected] in H2(T ) generated by a special Malmquist-Takenaka System

Page 2: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Motivation

The continuous voice transform

The voice transform of the Blaschke group

Multiresolution analysis of H2(T)

The projection operator to the n-th resolution level

Reconstruction algorithmMargit Pap http://nuhag.eu

Page 3: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Motivation

In signal processing the rational orthogonal bases (Laguerre,Kautz and Malmquist-Takenaka systems) are more efficient.

The successful application of rational orthogonal bases needsa priori knowledge of the poles of the transfer function thatmay cause a drawback of the method.

We give a set of poles and using them we will generate amultiresolution in H2(T) and H2(D).

The construction is an analogy with the discrete affinewavelets, and in fact is the discretization of the continuousvoice transform generated by a representation of the Blaschkegroup over the space H2(T).

Margit Pap http://nuhag.eu

Page 4: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Totik’s recovery theorem

Theorem

If (zn)n∈N is a sequence of complex numbers in the open unit discsuch that

∞∑j=0

(1− |zj |) =∞,

then for all f ∈ Hp(D) there are polynomials pn,j such that

‖f −n∑

j=0

f (zj)pn,j‖Hp → 0, if n→∞.

Margit Pap http://nuhag.eu

Page 5: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Recovery

The coefficients of pn,j are given by integrals, which can notbe determined exactly from (f (zj))j∈n.

Question: How to give a recovery formula depending only on(zj)j∈n and (f (zj))j∈n?

KEHE ZU, 1997 gave for H2(D) a possible algorithm of therecovery in generel for the set of uniqueness.

In this talk I will present a special set of the points(zj)j∈n ∈ D which will be the base of the recovery usingmultiresolution in H2(D) and in H2(T).

For this purpose we will need tools from non-commutativeharmonic analysis over groups and the generalization ofFourier transform: the voice transform.

Margit Pap http://nuhag.eu

Page 6: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The continuous voice transform

H. G. Feichtinger and K. H. Grochenig unified the theory ofGabor and wavelet transforms into a single theory. Thecommon generalization of these transforms is the so-calledvoice transform.

In the construction of the voice-transform the starting pointwill be a locally compact topological group (G , ·).

Let m be a left-invariant Haar measure of G :∫G

f (x) dm(x) =

∫G

f (a−1 · x) dm(x), (a ∈ G ).

Margit Pap http://nuhag.eu

Page 7: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The continuous voice transform

H. G. Feichtinger and K. H. Grochenig unified the theory ofGabor and wavelet transforms into a single theory. Thecommon generalization of these transforms is the so-calledvoice transform.

In the construction of the voice-transform the starting pointwill be a locally compact topological group (G , ·).

Let m be a left-invariant Haar measure of G :∫G

f (x) dm(x) =

∫G

f (a−1 · x) dm(x), (a ∈ G ).

Margit Pap http://nuhag.eu

Page 8: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The continuous voice transform

H. G. Feichtinger and K. H. Grochenig unified the theory ofGabor and wavelet transforms into a single theory. Thecommon generalization of these transforms is the so-calledvoice transform.

In the construction of the voice-transform the starting pointwill be a locally compact topological group (G , ·).

Let m be a left-invariant Haar measure of G :∫G

f (x) dm(x) =

∫G

f (a−1 · x) dm(x), (a ∈ G ).

Margit Pap http://nuhag.eu

Page 9: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The continuous voice transform

H. G. Feichtinger and K. H. Grochenig unified the theory ofGabor and wavelet transforms into a single theory. Thecommon generalization of these transforms is the so-calledvoice transform.

In the construction of the voice-transform the starting pointwill be a locally compact topological group (G , ·).

Let m be a left-invariant Haar measure of G :∫G

f (x) dm(x) =

∫G

f (a−1 · x) dm(x), (a ∈ G ).

Margit Pap http://nuhag.eu

Page 10: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Unitary representation

Unitary representation of the group (G , ·): Let us considera Hilbert-space (H, 〈·, ·〉).U denote the set of unitary bijections U : H → H. Namely,the elements of U are bounded linear operators which satisfy〈Uf ,Ug〉 = 〈f , g〉 (f , g ∈ H).

The set U with the composition operation(U ◦ V )f := U(Vf ) (f ∈ H) is a group.The homomorphism of the group (G , ·) on the group (U , ◦)satisfying

i) Ux ·y = Ux ◦ Uy (x , y ∈ G ),

ii) G 3 x → Ux f ∈ H is continuous for all f ∈ H

is called the unitary representation of (G , ·) on H.

Margit Pap http://nuhag.eu

Page 11: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Unitary representation

Unitary representation of the group (G , ·): Let us considera Hilbert-space (H, 〈·, ·〉).U denote the set of unitary bijections U : H → H. Namely,the elements of U are bounded linear operators which satisfy〈Uf ,Ug〉 = 〈f , g〉 (f , g ∈ H).The set U with the composition operation(U ◦ V )f := U(Vf ) (f ∈ H) is a group.

The homomorphism of the group (G , ·) on the group (U , ◦)satisfying

i) Ux ·y = Ux ◦ Uy (x , y ∈ G ),

ii) G 3 x → Ux f ∈ H is continuous for all f ∈ H

is called the unitary representation of (G , ·) on H.

Margit Pap http://nuhag.eu

Page 12: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Unitary representation

Unitary representation of the group (G , ·): Let us considera Hilbert-space (H, 〈·, ·〉).U denote the set of unitary bijections U : H → H. Namely,the elements of U are bounded linear operators which satisfy〈Uf ,Ug〉 = 〈f , g〉 (f , g ∈ H).The set U with the composition operation(U ◦ V )f := U(Vf ) (f ∈ H) is a group.The homomorphism of the group (G , ·) on the group (U , ◦)satisfying

i) Ux ·y = Ux ◦ Uy (x , y ∈ G ),

ii) G 3 x → Ux f ∈ H is continuous for all f ∈ H

is called the unitary representation of (G , ·) on H.

Margit Pap http://nuhag.eu

Page 13: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Unitary representation

Unitary representation of the group (G , ·): Let us considera Hilbert-space (H, 〈·, ·〉).U denote the set of unitary bijections U : H → H. Namely,the elements of U are bounded linear operators which satisfy〈Uf ,Ug〉 = 〈f , g〉 (f , g ∈ H).The set U with the composition operation(U ◦ V )f := U(Vf ) (f ∈ H) is a group.The homomorphism of the group (G , ·) on the group (U , ◦)satisfying

i) Ux ·y = Ux ◦ Uy (x , y ∈ G ),

ii) G 3 x → Ux f ∈ H is continuous for all f ∈ H

is called the unitary representation of (G , ·) on H.

Margit Pap http://nuhag.eu

Page 14: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Definition of the voice transform

Definition

The voice transform of f ∈ H generated by the representation Uand by the parameter ρ ∈ H is the (complex-valued) function on Gdefined by

(Vρf )(x) := 〈f ,Uxρ〉 (x ∈ G , f , ρ ∈ H).

Taking as starting point (not necessarily commutative) locallycompact groups we can construct in this way importanttransformations.The affine wavelet transform is a voice transform of the affinegroup.

The Gabor transform is a voice transform of the Heisenberggroup.

Margit Pap http://nuhag.eu

Page 15: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Definition of the voice transform

Definition

The voice transform of f ∈ H generated by the representation Uand by the parameter ρ ∈ H is the (complex-valued) function on Gdefined by

(Vρf )(x) := 〈f ,Uxρ〉 (x ∈ G , f , ρ ∈ H).

Taking as starting point (not necessarily commutative) locallycompact groups we can construct in this way importanttransformations.The affine wavelet transform is a voice transform of the affinegroup.The Gabor transform is a voice transform of the Heisenberggroup. Margit Pap http://nuhag.eu

Page 16: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Definition of the voice transform

Definition

The voice transform of f ∈ H generated by the representation Uand by the parameter ρ ∈ H is the (complex-valued) function on Gdefined by

(Vρf )(x) := 〈f ,Uxρ〉 (x ∈ G , f , ρ ∈ H).

Taking as starting point (not necessarily commutative) locallycompact groups we can construct in this way importanttransformations.The affine wavelet transform is a voice transform of the affinegroup.The Gabor transform is a voice transform of the Heisenberggroup. Margit Pap http://nuhag.eu

Page 17: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Definition of the voice transform

Definition

The voice transform of f ∈ H generated by the representation Uand by the parameter ρ ∈ H is the (complex-valued) function on Gdefined by

(Vρf )(x) := 〈f ,Uxρ〉 (x ∈ G , f , ρ ∈ H).

Taking as starting point (not necessarily commutative) locallycompact groups we can construct in this way importanttransformations.The affine wavelet transform is a voice transform of the affinegroup.The Gabor transform is a voice transform of the Heisenberggroup. Margit Pap http://nuhag.eu

Page 18: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Affine wavelet transform

Affine wavelet transform

The affine group:G = {`(a,b)(x) = ax + b : R→ R : (a, b) ∈ R∗ × R}`1◦`2(x) = a1a2x +a1b2+b1, (a1, b1)◦(a2, b2) = (a1a2, a1b2+b1)The representation of G on L2(R)U(a,b)f (x) = |a|−1/2f (a−1x − b)The affine wavelet transform is:Wψf (a, b) = |a|−1/2

∫R f (t)ψ(a−1t − b)dt = 〈f ,U(a,b)ψ〉.

Discretization: Find a ψ such that

ψn,k = 2−n/2ψ(2−nx − k)

form a (orthonormal) basis in L2(R) which generate amultiresolution Margit Pap http://nuhag.eu

Page 19: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The Blaschke group

The Blaschke group Let us denote by

Ba(z) := εz − b

1− bz(z ∈ C, a = (b, ε) ∈ B := D× T, bz 6= 1)

the so called Blaschke functions,

D := {z ∈ C : |z | < 1}, T := {z ∈ C : |z | = 1}.

If a ∈ B, then Ba is an 1-1 map on T, D respectively.

The restrictions of the Blaschke functions on the set D or onT with the operation (Ba1 ◦ Ba2)(z) := Ba1(Ba2(z)) form agroup.

Margit Pap http://nuhag.eu

Page 20: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The Blaschke group

The Blaschke group Let us denote by

Ba(z) := εz − b

1− bz(z ∈ C, a = (b, ε) ∈ B := D× T, bz 6= 1)

the so called Blaschke functions,

D := {z ∈ C : |z | < 1}, T := {z ∈ C : |z | = 1}.

If a ∈ B, then Ba is an 1-1 map on T, D respectively.

The restrictions of the Blaschke functions on the set D or onT with the operation (Ba1 ◦ Ba2)(z) := Ba1(Ba2(z)) form agroup.

Margit Pap http://nuhag.eu

Page 21: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The Blaschke group

The Blaschke group Let us denote by

Ba(z) := εz − b

1− bz(z ∈ C, a = (b, ε) ∈ B := D× T, bz 6= 1)

the so called Blaschke functions,

D := {z ∈ C : |z | < 1}, T := {z ∈ C : |z | = 1}.

If a ∈ B, then Ba is an 1-1 map on T, D respectively.

The restrictions of the Blaschke functions on the set D or onT with the operation (Ba1 ◦ Ba2)(z) := Ba1(Ba2(z)) form agroup.

Margit Pap http://nuhag.eu

Page 22: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

In the set of the parameters B := D× T let us define theoperation induced by the function composition in thefollowing way Ba1 ◦ Ba2 = Ba1◦a2 .

(B, ◦) will be the Blaschke group which is isomorphic with thegroup ({Ba, a ∈ B}, ◦).

If we use the notations aj := (bj , εj), j ∈ {1, 2} anda := (b, ε) =: a1 ◦ a2 then

b =b1ε2 + b2

1 + b1b2ε2, ε = ε1

ε2 + b1b2

1 + ε2b1b2

.

The neutral element of the group (B, ◦) is e := (0, 1) ∈ B andthe inverse element of a = (b, ε) ∈ B is a−1 = (−bε, ε).

Margit Pap http://nuhag.eu

Page 23: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

In the set of the parameters B := D× T let us define theoperation induced by the function composition in thefollowing way Ba1 ◦ Ba2 = Ba1◦a2 .

(B, ◦) will be the Blaschke group which is isomorphic with thegroup ({Ba, a ∈ B}, ◦).

If we use the notations aj := (bj , εj), j ∈ {1, 2} anda := (b, ε) =: a1 ◦ a2 then

b =b1ε2 + b2

1 + b1b2ε2, ε = ε1

ε2 + b1b2

1 + ε2b1b2

.

The neutral element of the group (B, ◦) is e := (0, 1) ∈ B andthe inverse element of a = (b, ε) ∈ B is a−1 = (−bε, ε).

Margit Pap http://nuhag.eu

Page 24: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

In the set of the parameters B := D× T let us define theoperation induced by the function composition in thefollowing way Ba1 ◦ Ba2 = Ba1◦a2 .

(B, ◦) will be the Blaschke group which is isomorphic with thegroup ({Ba, a ∈ B}, ◦).

If we use the notations aj := (bj , εj), j ∈ {1, 2} anda := (b, ε) =: a1 ◦ a2 then

b =b1ε2 + b2

1 + b1b2ε2, ε = ε1

ε2 + b1b2

1 + ε2b1b2

.

The neutral element of the group (B, ◦) is e := (0, 1) ∈ B andthe inverse element of a = (b, ε) ∈ B is a−1 = (−bε, ε).

Margit Pap http://nuhag.eu

Page 25: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

In the set of the parameters B := D× T let us define theoperation induced by the function composition in thefollowing way Ba1 ◦ Ba2 = Ba1◦a2 .

(B, ◦) will be the Blaschke group which is isomorphic with thegroup ({Ba, a ∈ B}, ◦).

If we use the notations aj := (bj , εj), j ∈ {1, 2} anda := (b, ε) =: a1 ◦ a2 then

b =b1ε2 + b2

1 + b1b2ε2, ε = ε1

ε2 + b1b2

1 + ε2b1b2

.

The neutral element of the group (B, ◦) is e := (0, 1) ∈ B andthe inverse element of a = (b, ε) ∈ B is a−1 = (−bε, ε).

Margit Pap http://nuhag.eu

Page 26: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

In the set of the parameters B := D× T let us define theoperation induced by the function composition in thefollowing way Ba1 ◦ Ba2 = Ba1◦a2 .

(B, ◦) will be the Blaschke group which is isomorphic with thegroup ({Ba, a ∈ B}, ◦).

If we use the notations aj := (bj , εj), j ∈ {1, 2} anda := (b, ε) =: a1 ◦ a2 then

b =b1ε2 + b2

1 + b1b2ε2, ε = ε1

ε2 + b1b2

1 + ε2b1b2

.

The neutral element of the group (B, ◦) is e := (0, 1) ∈ B andthe inverse element of a = (b, ε) ∈ B is a−1 = (−bε, ε).

Margit Pap http://nuhag.eu

Page 27: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

The integral of the function f : B→ C, with respect to thisleft invariant Haar measure m of the group (B, ◦), is given by∫

Bf (a) dm(a) =

1

∫I

∫D

f (b, e it)

(1− |b|2)2db1db2dt,

where a = (b, e it) = (b1 + ib2, eit) ∈ D× T.

Denote by εn(t) = e int (t ∈ I = [0, 2π], n ∈ N), let considerthe Hilbert space H = H2(T), the closure in L2(T)-norm ofthe set

span{εn, n ∈ N}.

Margit Pap http://nuhag.eu

Page 28: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

The integral of the function f : B→ C, with respect to thisleft invariant Haar measure m of the group (B, ◦), is given by∫

Bf (a) dm(a) =

1

∫I

∫D

f (b, e it)

(1− |b|2)2db1db2dt,

where a = (b, e it) = (b1 + ib2, eit) ∈ D× T.

Denote by εn(t) = e int (t ∈ I = [0, 2π], n ∈ N), let considerthe Hilbert space H = H2(T), the closure in L2(T)-norm ofthe set

span{εn, n ∈ N}.

Margit Pap http://nuhag.eu

Page 29: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

The integral of the function f : B→ C, with respect to thisleft invariant Haar measure m of the group (B, ◦), is given by∫

Bf (a) dm(a) =

1

∫I

∫D

f (b, e it)

(1− |b|2)2db1db2dt,

where a = (b, e it) = (b1 + ib2, eit) ∈ D× T.

Denote by εn(t) = e int (t ∈ I = [0, 2π], n ∈ N), let considerthe Hilbert space H = H2(T), the closure in L2(T)-norm ofthe set

span{εn, n ∈ N}.

Margit Pap http://nuhag.eu

Page 30: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The representation of the Blaschke group on H2(T)

The inner product is given by

〈f , g〉 :=1

∫I

f (e it)g(e it) dt (f , g ∈ H).

The representation of the Blaschke group on H2(T): for(z = e it ∈ T, a = (b, e iθ) ∈ B

), f ∈ H2(T):

(Ua−1f )(z) :=

√e iθ(1− |b|2)

(1− bz)f(e iθ(z − b)

1− bz

)

Margit Pap http://nuhag.eu

Page 31: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The representation of the Blaschke group on H2(T)

The inner product is given by

〈f , g〉 :=1

∫I

f (e it)g(e it) dt (f , g ∈ H).

The representation of the Blaschke group on H2(T): for(z = e it ∈ T, a = (b, e iθ) ∈ B

), f ∈ H2(T):

(Ua−1f )(z) :=

√e iθ(1− |b|2)

(1− bz)f(e iθ(z − b)

1− bz

)

Margit Pap http://nuhag.eu

Page 32: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

The voice transform generated by Ua (a ∈ B) is given by thefollowing formula

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)).

Pap M., Schipp F., The voice transform on the Blaschkegroup I., PU.M.A., Vol 17, (2006), No 3-4, pp. 387-395.

Pap M., Schipp F., The voice transform on the Blaschkegroup II., Annales Univ. Sci. (Budapest), Sect. Comput., 29(2008) 157-173.The matrix elements of the representation can be given by theZernike functions which play an important role in expressingthe wavefront data in optical tests.An important consequence of this connection is the additionformula for Zernike functions.

Margit Pap http://nuhag.eu

Page 33: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

The voice transform generated by Ua (a ∈ B) is given by thefollowing formula

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)).

Pap M., Schipp F., The voice transform on the Blaschkegroup I., PU.M.A., Vol 17, (2006), No 3-4, pp. 387-395.Pap M., Schipp F., The voice transform on the Blaschkegroup II., Annales Univ. Sci. (Budapest), Sect. Comput., 29(2008) 157-173.

The matrix elements of the representation can be given by theZernike functions which play an important role in expressingthe wavefront data in optical tests.An important consequence of this connection is the additionformula for Zernike functions.

Margit Pap http://nuhag.eu

Page 34: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

The voice transform generated by Ua (a ∈ B) is given by thefollowing formula

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)).

Pap M., Schipp F., The voice transform on the Blaschkegroup I., PU.M.A., Vol 17, (2006), No 3-4, pp. 387-395.Pap M., Schipp F., The voice transform on the Blaschkegroup II., Annales Univ. Sci. (Budapest), Sect. Comput., 29(2008) 157-173.The matrix elements of the representation can be given by theZernike functions which play an important role in expressingthe wavefront data in optical tests.An important consequence of this connection is the additionformula for Zernike functions.

Margit Pap http://nuhag.eu

Page 35: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The voice transform of the Blaschke group

The voice transform generated by Ua (a ∈ B) is given by thefollowing formula

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)).

Pap M., Schipp F., The voice transform on the Blaschkegroup I., PU.M.A., Vol 17, (2006), No 3-4, pp. 387-395.Pap M., Schipp F., The voice transform on the Blaschkegroup II., Annales Univ. Sci. (Budapest), Sect. Comput., 29(2008) 157-173.The matrix elements of the representation can be given by theZernike functions which play an important role in expressingthe wavefront data in optical tests.An important consequence of this connection is the additionformula for Zernike functions.

Margit Pap http://nuhag.eu

Page 36: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Discretization

Pap M.: Hyperbolic Wavelets and Multiresolution in H2(T),Accepted for publication: Journal of Fourier Analysis andApplications DOI: 10.1007/s00041-011-9169-2

Continuous voice transform:

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)), a = (re iφ, e iψ) ∈ B.

Question: How to choose a discrete subset ak` = (zk`, 1) ∈ Band ρ ∈ H2(T) such that the functions Ua−1

k`ρ generate a

multiresolution decomposition in H2(T)) and in H2(D)) ?

Let denote by B1 ={

(rk , 1) : rk = 2k−2−k

2k+2−k , k ∈ Z}.

It can be proved that (B1, ◦) is a subgroup of (B, ◦), and(rk , 1) ◦ (rn, 1) = (rk+n, 1).The pseudo hyperbolic distance of the points rk , rn has thefollowing property: ρ(rk , rn) = |rk−n|.

Margit Pap http://nuhag.eu

Page 37: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Discretization

Pap M.: Hyperbolic Wavelets and Multiresolution in H2(T),Accepted for publication: Journal of Fourier Analysis andApplications DOI: 10.1007/s00041-011-9169-2

Continuous voice transform:

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)), a = (re iφ, e iψ) ∈ B.

Question: How to choose a discrete subset ak` = (zk`, 1) ∈ Band ρ ∈ H2(T) such that the functions Ua−1

k`ρ generate a

multiresolution decomposition in H2(T)) and in H2(D)) ?

Let denote by B1 ={

(rk , 1) : rk = 2k−2−k

2k+2−k , k ∈ Z}.

It can be proved that (B1, ◦) is a subgroup of (B, ◦), and(rk , 1) ◦ (rn, 1) = (rk+n, 1).The pseudo hyperbolic distance of the points rk , rn has thefollowing property: ρ(rk , rn) = |rk−n|.

Margit Pap http://nuhag.eu

Page 38: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Discretization

Pap M.: Hyperbolic Wavelets and Multiresolution in H2(T),Accepted for publication: Journal of Fourier Analysis andApplications DOI: 10.1007/s00041-011-9169-2

Continuous voice transform:

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)), a = (re iφ, e iψ) ∈ B.

Question: How to choose a discrete subset ak` = (zk`, 1) ∈ Band ρ ∈ H2(T) such that the functions Ua−1

k`ρ generate a

multiresolution decomposition in H2(T)) and in H2(D)) ?

Let denote by B1 ={

(rk , 1) : rk = 2k−2−k

2k+2−k , k ∈ Z}.

It can be proved that (B1, ◦) is a subgroup of (B, ◦), and(rk , 1) ◦ (rn, 1) = (rk+n, 1).

The pseudo hyperbolic distance of the points rk , rn has thefollowing property: ρ(rk , rn) = |rk−n|.

Margit Pap http://nuhag.eu

Page 39: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Discretization

Pap M.: Hyperbolic Wavelets and Multiresolution in H2(T),Accepted for publication: Journal of Fourier Analysis andApplications DOI: 10.1007/s00041-011-9169-2

Continuous voice transform:

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)), a = (re iφ, e iψ) ∈ B.

Question: How to choose a discrete subset ak` = (zk`, 1) ∈ Band ρ ∈ H2(T) such that the functions Ua−1

k`ρ generate a

multiresolution decomposition in H2(T)) and in H2(D)) ?

Let denote by B1 ={

(rk , 1) : rk = 2k−2−k

2k+2−k , k ∈ Z}.

It can be proved that (B1, ◦) is a subgroup of (B, ◦), and(rk , 1) ◦ (rn, 1) = (rk+n, 1).The pseudo hyperbolic distance of the points rk , rn has thefollowing property: ρ(rk , rn) = |rk−n|.

Margit Pap http://nuhag.eu

Page 40: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Discretization

Pap M.: Hyperbolic Wavelets and Multiresolution in H2(T),Accepted for publication: Journal of Fourier Analysis andApplications DOI: 10.1007/s00041-011-9169-2

Continuous voice transform:

(Vρf )(a−1) := 〈f ,Ua−1ρ〉 (f , ρ ∈ H2(T)), a = (re iφ, e iψ) ∈ B.

Question: How to choose a discrete subset ak` = (zk`, 1) ∈ Band ρ ∈ H2(T) such that the functions Ua−1

k`ρ generate a

multiresolution decomposition in H2(T)) and in H2(D)) ?

Let denote by B1 ={

(rk , 1) : rk = 2k−2−k

2k+2−k , k ∈ Z}.

It can be proved that (B1, ◦) is a subgroup of (B, ◦), and(rk , 1) ◦ (rn, 1) = (rk+n, 1).The pseudo hyperbolic distance of the points rk , rn has thefollowing property: ρ(rk , rn) = |rk−n|.

Margit Pap http://nuhag.eu

Page 41: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of L2(R)

Let Vj , j ∈ Z be a sequence of subspaces of L2(R). Thecollections of spaces {Vj , j ∈ Z} is called a multiresolutionanalysis with scaling function φ if the following conditions hold:1. (nested) Vj ⊂ Vj+1

2. (density) ∪Vj = L2(R)3. (separation) ∩Vj = {0}4. (basis) The function φ belongs to V0 and the set{2n/2φ(2nx − k), k ∈ Z} is a (orthonormal) bases in Vn.

Margit Pap http://nuhag.eu

Page 42: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

We want to give the analogue of the affine wavelet multiresolutionanalysis in H2(T) .

Definition

Let Vj , j ∈ N be a sequence of subspaces of H2(T ). Thecollections of spaces {Vj , j ∈ N} is called a multiresolution if thefollowing conditions hold:1. (nested) Vj ⊂ Vj+1,2. (density) ∪Vj = H2(T )3. (dilatation) U(r1,1)−1(Vj) ⊂ Vj+1

4. (basis) There exist ψj` (orthonormal) bases in Vj .

Margit Pap http://nuhag.eu

Page 43: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

Let us consider the set of points in the unit disc

A = {zk` = rkei 2π`22k , ` = 0, 1, ..., 22k − 1, k = 0, 1, 2, ...∞},

Ak = {zk` = rkei 2π`22k , ` ∈ {0, 1, ..., 22k − 1}}.

A is not a Blaschke sequence:∑

k,`(1− |zk`|) =∞.

Margit Pap http://nuhag.eu

Page 44: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

Let us consider the function p0 = ϕ00 = 1, V0 = {c , c ∈ C}and let

p1(z) = Ur−11

p0 =

√1− r21

(1− r1z), pn(z) = (Ur−1

1pn−1)(z) =

√1− r2n

(1− rnz),

ϕn,`(z) = (U(rn−1◦r1)−1p0)(e i(t−2π`22n

)).

Let us define the n-th resolution level by

Vn = {f : D → C , f (z) =n∑

k=0

22k−1∑`=0

ck,`ϕk,`, ck,` ∈ C }.

If a function f ∈ Vn, then U(r1,1)−1f ∈ Vn+1.Margit Pap http://nuhag.eu

Page 45: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

Let us consider the function p0 = ϕ00 = 1, V0 = {c , c ∈ C}and let

p1(z) = Ur−11

p0 =

√1− r21

(1− r1z), pn(z) = (Ur−1

1pn−1)(z) =

√1− r2n

(1− rnz),

ϕn,`(z) = (U(rn−1◦r1)−1p0)(e i(t−2π`22n

)).

Let us define the n-th resolution level by

Vn = {f : D → C , f (z) =n∑

k=0

22k−1∑`=0

ck,`ϕk,`, ck,` ∈ C }.

If a function f ∈ Vn, then U(r1,1)−1f ∈ Vn+1.Margit Pap http://nuhag.eu

Page 46: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

The closed subset Vn is spanned by the nonorthogonal basis:

{ϕk,`, ` = 0, 1, ..., 22k − 1, k = 1, ..., n},V0 ⊂ V1 ⊂ V2 ⊂ .....Vn ⊂ ....H2(T ).

Applying the Gram-Schmidt orthogonalization for this set ofanalytic linearly independent functions we obtain theMalmquist -Takenaka system corresponding to the set∪nk=0Ak :

ψm,`(z) =

√1− r2m

1− zm`z

m−1∏k=0

22k−1∏j=0

z − zkj1− zkjz

`−1∏j ′=0

z − zmj ′

1− zmj ′z.

Margit Pap http://nuhag.eu

Page 47: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

The closed subset Vn is spanned by the nonorthogonal basis:

{ϕk,`, ` = 0, 1, ..., 22k − 1, k = 1, ..., n},V0 ⊂ V1 ⊂ V2 ⊂ .....Vn ⊂ ....H2(T ).

Applying the Gram-Schmidt orthogonalization for this set ofanalytic linearly independent functions we obtain theMalmquist -Takenaka system corresponding to the set∪nk=0Ak :

ψm,`(z) =

√1− r2m

1− zm`z

m−1∏k=0

22k−1∏j=0

z − zkj1− zkjz

`−1∏j ′=0

z − zmj ′

1− zmj ′z.

Margit Pap http://nuhag.eu

Page 48: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 49: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 50: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 51: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 52: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 53: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 54: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 55: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 56: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 57: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 58: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,
Page 59: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

Vn = span{ψk,`, ` = 0, 1, ..., 22k − 1, k = 0, n}.

The Malmquist -Takenaka system corresponding to the set Ais a complete orthonormal system of holomorphic functions inH2(T ), consequently the density condition is satisfied:⋃

n∈NVn = H2(T ).

The wavelet space Wn is the orthogonal complement of Vn inVn+1:

Wn = span{ψn+1,`, ` = 0, 1, ..., 22n+2 − 1},

Margit Pap http://nuhag.eu

Page 60: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

Vn = span{ψk,`, ` = 0, 1, ..., 22k − 1, k = 0, n}.

The Malmquist -Takenaka system corresponding to the set Ais a complete orthonormal system of holomorphic functions inH2(T ), consequently the density condition is satisfied:⋃

n∈NVn = H2(T ).

The wavelet space Wn is the orthogonal complement of Vn inVn+1:

Wn = span{ψn+1,`, ` = 0, 1, ..., 22n+2 − 1},Margit Pap http://nuhag.eu

Page 61: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

Multiresolution analysis of H2(T)

Vn = span{ψk,`, ` = 0, 1, ..., 22k − 1, k = 0, n}.

The Malmquist -Takenaka system corresponding to the set Ais a complete orthonormal system of holomorphic functions inH2(T ), consequently the density condition is satisfied:⋃

n∈NVn = H2(T ).

The wavelet space Wn is the orthogonal complement of Vn inVn+1:

Wn = span{ψn+1,`, ` = 0, 1, ..., 22n+2 − 1},Margit Pap http://nuhag.eu

Page 62: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Unitary representationDefinition of the voice transformSpecial voice transformsThe voice transform of the Blaschke groupDiscretizationMultiresolution analysis of L2(R)The projection operator to the n-th resolution level

The projection operator to the n-th resolution level

Vn+1 = Vn

⊕Wn.

For f ∈ H2(T ) let consider:

Pnf (z) =n∑

k=0

22k−1∑`=0

〈f , ψk,`〉ψk,`(z)

,

ψm,`(z) =

√1− r2m

1− zm`z

m−1∏k=0

22k−1∏j=0

z − zkj1− zkjz

`−1∏j ′=0

z − zmj ′

1− zmj ′z.

Margit Pap http://nuhag.eu

Page 63: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Theorem

For f ∈ H2(T ) the projection operator Pnf is an interpolationoperator in the points

zmj = rme i2πj

22m , (j = 0, ...., 22m − 1, m = 0, ..., n) for the analyticcontinuation of f in the unit disc,

‖f − Pnf ‖ → 0, n→∞,

uniform convergence for the analytic continuation of f inside theunit disc on every compact subset. For every f ∈ H2(D)

‖Pnf (z)− f ‖= inffn∈Vn

‖fn − f ‖,

Margit Pap http://nuhag.eu

Page 64: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

In what follows we propose a computational scheme in thewavelet base {ψk,`, ` = 0, 1, ..., 22k − 1, k = 0, ..., n}.The projection of f ∈ H2(T ) onto Vn+1 can be written in thefollowing way:

Qnf (z) :=22(n+1)−1∑`=0

〈f , ψn+1,`〉ψn+1,`(z),

Pn+1f = Pnf + Qnf , Qnf (zk`) = 0, k = 1, n, ` = 0, 22n − 1.

This means that Qn contains information only from levelAn+1. Consequently Pn contains information on lowresolution, i.e., until the level An, and Qn is the highresolution part. After n steps

Pn+1f = P1f +n∑

k=1

Qnf , Vn+1 = V0

⊕W0

⊕W1

⊕...⊕

Wn.

Margit Pap http://nuhag.eu

Page 65: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

In what follows we propose a computational scheme in thewavelet base {ψk,`, ` = 0, 1, ..., 22k − 1, k = 0, ..., n}.The projection of f ∈ H2(T ) onto Vn+1 can be written in thefollowing way:

Qnf (z) :=22(n+1)−1∑`=0

〈f , ψn+1,`〉ψn+1,`(z),

Pn+1f = Pnf + Qnf , Qnf (zk`) = 0, k = 1, n, ` = 0, 22n − 1.

This means that Qn contains information only from levelAn+1. Consequently Pn contains information on lowresolution, i.e., until the level An, and Qn is the highresolution part. After n steps

Pn+1f = P1f +n∑

k=1

Qnf , Vn+1 = V0

⊕W0

⊕W1

⊕...⊕

Wn.

Margit Pap http://nuhag.eu

Page 66: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

In what follows we propose a computational scheme in thewavelet base {ψk,`, ` = 0, 1, ..., 22k − 1, k = 0, ..., n}.The projection of f ∈ H2(T ) onto Vn+1 can be written in thefollowing way:

Qnf (z) :=22(n+1)−1∑`=0

〈f , ψn+1,`〉ψn+1,`(z),

Pn+1f = Pnf + Qnf , Qnf (zk`) = 0, k = 1, n, ` = 0, 22n − 1.

This means that Qn contains information only from levelAn+1. Consequently Pn contains information on lowresolution, i.e., until the level An, and Qn is the highresolution part. After n steps

Pn+1f = P1f +n∑

k=1

Qnf , Vn+1 = V0

⊕W0

⊕W1

⊕...⊕

Wn.

Margit Pap http://nuhag.eu

Page 67: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

The set of coefficients of the best approximant Pnf :({bk` = 〈f , ψk,`〉, ` = 0.1, ...22k − 1 k = 0, 1, ..., n}) is the(discrete) hyperbolic wavelet transform of the function f .The coefficients of the projection operator Pnf can becomputed if we know the values of the functions on

⋃nk=0 Ak .

ψk,` =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′1

1− zk ′`′ξ+∑j=0

ck,j1

1− zkjξ,

〈f , ψk,`〉 =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′f (zk ′,`′) +∑j=0

ck,j f (zk,j).

Margit Pap http://nuhag.eu

Page 68: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

The set of coefficients of the best approximant Pnf :({bk` = 〈f , ψk,`〉, ` = 0.1, ...22k − 1 k = 0, 1, ..., n}) is the(discrete) hyperbolic wavelet transform of the function f .The coefficients of the projection operator Pnf can becomputed if we know the values of the functions on

⋃nk=0 Ak .

ψk,` =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′1

1− zk ′`′ξ+∑j=0

ck,j1

1− zkjξ,

〈f , ψk,`〉 =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′f (zk ′,`′) +∑j=0

ck,j f (zk,j).

Margit Pap http://nuhag.eu

Page 69: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

The set of coefficients of the best approximant Pnf :({bk` = 〈f , ψk,`〉, ` = 0.1, ...22k − 1 k = 0, 1, ..., n}) is the(discrete) hyperbolic wavelet transform of the function f .The coefficients of the projection operator Pnf can becomputed if we know the values of the functions on

⋃nk=0 Ak .

ψk,` =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′1

1− zk ′`′ξ+∑j=0

ck,j1

1− zkjξ,

〈f , ψk,`〉 =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′f (zk ′,`′) +∑j=0

ck,j f (zk,j).

Margit Pap http://nuhag.eu

Page 70: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

The set of coefficients of the best approximant Pnf :({bk` = 〈f , ψk,`〉, ` = 0.1, ...22k − 1 k = 0, 1, ..., n}) is the(discrete) hyperbolic wavelet transform of the function f .The coefficients of the projection operator Pnf can becomputed if we know the values of the functions on

⋃nk=0 Ak .

ψk,` =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′1

1− zk ′`′ξ+∑j=0

ck,j1

1− zkjξ,

〈f , ψk,`〉 =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′f (zk ′,`′) +∑j=0

ck,j f (zk,j).

Margit Pap http://nuhag.eu

Page 71: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Reconstruction algorithm

For f ∈ H2(T )

Pnf (z) =n∑

k=0

22k−1∑`=0

〈f , ψk,`〉ψk,`(z),

〈f , ψk,`〉 =k−1∑k ′=0

22k′−1∑

`′=0

ck ′,`′f (zk ′,`′) +∑j=0

ck,j f (zk,j),

ψm,`(z) =

√1− r2m

1− zm`z

m−1∏k=0

22k−1∏j=0

z − zkj1− zkjz

`−1∏j ′=0

z − zmj ′

1− zmj ′z.

Margit Pap http://nuhag.eu

Page 72: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

Summary

Measuring the values of the function f in the points of the setA =

⋃nk=0 Ak ⊂ D we can write the the projection operator at the

n-th resolution level which is convergent in H2(T ) norm on theunit circle to f , is the best approximant interpolation operator onthe set the

⋃nk=0 Ak inside the unit circle for the analytic

continuation of f and Pnf (z)→ f (z) uniformly on every compactsubset of the unit disc. Complex coloring visualization of hyperbolicwavelets see homepage of Levente Locsi: http://locsi.web.elte.hu/.

Margit Pap http://nuhag.eu

Page 73: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

References

A. Bultheel and P. Carrette.,Algebraic and spectralproperties of general Toeplitz matrices, SIAM J. ControlOptim., 41(5):1413-1439, (2003).

Bultheel A., Gonzalez-Vera P., Wavelets by orthogonalrational kernels, Contemp. Math., Vol. 236, (1999), 101-126.

Chui C. K., An Introduction to Wavelets, Academic Press,New York, London, Toronto, Sydney, San Francisco, 1992.

Chui C. K., Chen G., Signal processing and systems theory,Springer-Verlag, Series in Information Sciences, 26 (1992).

Margit Pap http://nuhag.eu

Page 74: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

References

Daubechies I., Orthonormal bases of compactly supportedwavelets, Comm. Pure Appl. Math. vol. 41, (1988), 909-996.

Feichtinger H. G., Grochenig K. , A unified approach toatomic decompositions trough integrable grouprepresentations , Functions Spaces and Applications, M.Cwinkel e. all. eds. Lecture Notes in Math. 1302,Springer-Verlag (1989), 307-340.

Feichtinger H. G., Grochenig K., Banach spaces related tointegrable group representations and their atomicdecomposition I., Journal of Functional Analysis, Vol. 86, No.2,(1989), 307-340.

Margit Pap http://nuhag.eu

Page 75: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

References

Heil C. E., Walnut D. F., Continuous and discrete wavelettransforms, SIAM Review, Vol. 31, No. 4, December (1989),628-666.Mallat S., Theory of multiresolution signal decomposition:The wavelet representation, IEEE Trans. Pattern. Anal.Math. Intell. vol. 11, no. 7., (1989), 674-693.Pap M., Schipp F., The voice transform on the Blaschkegroup II., Annales Univ. Sci. (Budapest), Sect. Comput., 29,(2008), 157-173.Pap M., Schipp F., The voice transform on the Blaschkegroup III., Publ. Math., 75, 1-2, (2009), 263-283.Pap M., Hyperbolic Wavelets and Multiresolution in H2(T),Accepted for publication: Journal of Fourier Analysis andApplications, DOI: 10.1007/s00041-011-9169-2Margit Pap http://nuhag.eu

Page 76: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

References

J. Partington., Interpolation, Identification and Sampling,volume 17 of London Mathematical Society Monographs.Oxford University Press, 1997.

Soumelidis A., Pap M., Schipp F., Bokor J., Frequencydomain identification of partial fraction models, Proc. of the15th IFAC World Congress, Barcelona, Spain, June (2002),1-6.

Totik, V., Recovery of Hp-functions., Proc. Am. Math. Soc.90, 531-537, (1984).

N.F.D. Ward and J.R. Partington, Robust identification inthe disc algebra using rational wavelets and orthonormal basisfunctions. Internat. J. Control, 64:409-423, (1996).

Margit Pap http://nuhag.eu

Page 77: Multiresolution in H2(T) generated by a special Malmquist ... · University of P ecs, Hungary 1 papmargit@citromail.hu, margit.pap@univie.ac.at July 10, 2011 1University of P ecs,

SummaryMotivation

Totik’s recovery theoremRecovery

The continuous voice transformReconstruction algorithm

ReferencesEND

END

THANK YOU FOR YOURATTENTION

Margit Pap http://nuhag.eu