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Today : § 3.3 Determinants
&§5.1 : Eigen values
Next : § 5.2 : Characteristic Polynomial
Reminders
MATLAB Assignment # 4.Due TONIGHT by 11:59pm
My Math Lab Homework # 6 : Due Tuesday by ltisepm
Midterm # 2 : Next Wednesday,
8- 10pmRom 1 seat assgn .
& practicemidterms posted on course webpage .
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Properties of Determinants
* Defined by cofactor expansion ( recursive expression , expandalong any now or column )
* Behaves nicely under new ops : detA= ± ( product of pivots inrow reduction Kerrey ) ) .
* det A =o iff A is net Invertible* det : Mn → IR Is multi linear in each now and column of
the matrix,
with the others held fixed .
* dot LAB) = detlA)deHB ).
.: detl An)=(deHA)Y .
Two MORE PROPERTIES :
det ( At ) =
deb ( At ) =
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What is the determinant ? What does it mean ?
Parallelograms :
b.b.to
E'
q IF 9
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heorem . Given two vectors a,
b. e- 1122,
the area ofthe parallelogram they determine B
Ala. ,
b.) = ldetla,b.) /
feetatiltwhat dees the sign of detlg
,b. } mean ?
What about nxn determinants with n > 2 ?
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Parallelepipeds
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§ 5.1 / A linear transformation T :v→V tends to more
vectors around.
E-g. TH)=p←x2y|
tl ! }l )
-412,1) =
Eg .
If A is a stochastic matrix ( new sums = 1) then
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Definition Let T :V→V be a linear transformation .
If there B a non - zero I← V such that
Tlv. ) = xv
.
for seme Scalar XEIR,
we Call V. an
eigenvector of T.
The scalar × is
the corresponding eigen value.
( We similarly
talk about eigenvectors / ergenvalnes ofsquare
matrices.)
Eg.
Show that 7 is an eigen value of A = ( g{ )
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Theorem : Forany he R
,
the set of vectors v. for whrh
TH ) = tv
B a sub space of V,
called the eigenspace of X.
( We only call d an eyen value if its eigenspace B He})
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Eg.
The rotation matrix ( o
, f) kcwsi ) has no
eizenvahei.
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E 9 .
↳ tA = µ if 6g ) .
2 is an eigen value for A ;
find a bas B for the eigenspao .
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* Given a ( potential ) eigenvahe,
finding the corresponding
eigenspaee is noutme.
* Finding the eigen values is typically hard. ( Row reduction
changes the eigenvakes . )One Case When eiyonvalues can be read off :
Theorem '. If A is triangular,
its eigen values are its diagonal entries.
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Eg.
As Hl )
E.g .
�1� = W