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Treffpunkt MATLAB 2017
TREFFPUNKT MATLAB 2017ITA-TOOLBOX
Johannes Klein, Marco Berzborn,Ramona Bomhardt, Jan-Gerrit RichterInstitut für Technische AkustikRWTH Aachen
Treffpunkt MATLAB 2017
ITA - INSTITUTE OF TECHNICAL ACOUSTICS
Treffpunkt MATLAB 2017
ITA – INSTITUTE OF TECHNICAL ACOUSTICS
Faculty of Electrical Engineering and Communication Technology Two departments: Technical Acoustics (Prof. Michael Vorländer) Medical Acoustics (Prof. Janina Fels)
18 Researchers and 1 senior engineer
Architectural acoustics & virtual reality Electro acoustics & measurement Binaural & spatial audio
Treffpunkt MATLAB 2017
ARCHITECTURAL ACOUSTICS & VIRTUAL REALITY
Room and building acoustics Numerical acoustics Fast simulation methods Auralization
Treffpunkt MATLAB 2017
BINAURAL HEARING & SPATIAL AUDIO
Binaural hearing Array technologies and directivity Medical acoustics and audiology Psychoacoustics
Treffpunkt MATLAB 2017
ELECTRO ACOUSTICS & MEASUREMENT
Pro-audio and loudspeakers development and engineering Vibro-acoustics and TPA Condition monitoring www.ita-toolbox.org
Treffpunkt MATLAB 2017
ita-toolbox.org || git.rwth-aachen.de
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Treffpunkt MATLAB 2017
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Treffpunkt MATLAB 2017
DIGITAL SIGNAL PROCESSING
Treffpunkt MATLAB 2017
DIGITAL SIGNAL PROCESSING
Quantization: evenly spaced integer values for previouslycontinuous amplitude
Common number of quantization steps:216 ≡± 32767
Quantization errors mostly result in white noise
Treffpunkt MATLAB 2017
DIGITAL SIGNAL PROCESSING
Sampling: evenly spaced discretization of previously time-continuous signal
Nyquist theorem: SignalSampling ff 2
Treffpunkt MATLAB 2017
DIGITAL SIGNAL PROCESSING
Signal Processing Basics Discrete Fourier Transform (DFT)
Sampling causes mirrored ‘alias’ spectra
discrete representation in frequency domaincauses ‘alias’ impulses in time domain
Treffpunkt MATLAB 2017
DIGITAL SIGNAL PROCESSING
Signal Processing Basics Influence of the phase
Treffpunkt MATLAB 2017
DIGITAL SIGNAL PROCESSING
Signal Processing Basics Influence of the phase
Treffpunkt MATLAB 2017
DIGITAL SIGNAL PROCESSING
Signal Processing Basics Influence of the phase
Treffpunkt MATLAB 2017
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Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Signal processing basics LTI system
Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Signal processing basics Impulse response
Do we have to measure with an impulse?
Pro: directly obtain impulse response Con: not feasible
Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Signal processing basics Impulse response
Do we have to measure with an impulse? No!
Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Signal processing basics Advantages of extended measurement signals
Distribute more energy over time
Better Signal-to-Noise Ratio (SNR)
Adapt signals to measurement hardware Equalize equipment Optimal dynamic range
More information about the system properties
Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Signal processing basics Signal properties
Real-valued time signals – symmetric spectra Periodic time signals – discrete spectra
Frequency resolution depends on measurement time
Averaging to improve SNR
av dB 10lg N
3dB 6dB 9dB 12dB 15dB 18dB2 4 8 16 32 64
Treffpunkt MATLAB 2017
Measurement signals How long to measure?
Tmeas > TReverb
Bin distance
analogous to„sampling“
Measurement period
f
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Tmeas > 1/∆f
Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Signal processing basics How does deconvolution work?
Treffpunkt MATLAB 2017
LINEAR TIME-INVARIANT SYSTEMS (LTI)
Signal processing basics How does deconvolution work?
Treffpunkt MATLAB 2017
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