Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing

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1. Verfasser: Goodman, Roe 1938- (VerfasserIn)
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Veröffentlicht: New Jersey ; London ; Singapore ; Beijing ; Shanghai ; Hong Kong ; Taipei ; Chennai ; Tokyo World Scientific [2016]
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Datensatz im Suchindex

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adam_text Contents Preface v 1. Linear Algebra and Signal Processing 1 1.1 Overview .......................................................... 1 1.2 Sampling and Quantization.......................................... 2 1.3 Vector Spaces...................................................... 3 1.4 Bases and Dual Bases .............................................. 6 1.5 Linear Transformations and Matrices............................... 10 1.5.1 Matrix form of a linear transformation ................... 11 1.5.2 Direct sums of vector spaces.............................. 14 1.5.3 Partitioned matrices and block multiplication............. 14 1.6 Vector Graphics and Animation..................................... 16 1.6.1 Geometric transformations of images ...................... 17 1.6.2 Affine transformations.................................... 20 1.7 Inner Products, Orthogonal Projections, and Unitary Matrices . . 21 1.8 Fourier Series.................................................... 27 1.9 Computer Explorations............................................. 30 1.9.1 Sampling and quantizing an audio signal................... 30 1.9.2 Vector graphics .......................................... 33 1.10 Exercises......................................................... 36 2. Discrete Fourier Transform 41 2.1 Overview ......................................................... 41 2.2 Sampling and Aliasing............................................. 41 2.3 Discrete Fourier Transform and Fourier Matrix..................... 45 2.4 Shift-Invariant Transformations and Circulant Matrices ........... 48 2.4.1 Moving averages and shift operator........................ 48 2.4.2 Shift-iriyariant transformations.......................... 50 2.4.3 Eigenvectors and eigenvalues of circulant matrices........ 52 2.5 Circular Convolution and Filters.................................. 53 ix x Contents 2.6 Downsampling and Fast Fourier Transform ............................ 59 2.7 Computer Explorations............................................... 62 2.7.1 Fourier matrix and sampling................................. 62 2.7.2 Applications of the discrete Fourier transform ............. 64 2.7.3 Circulant matrices and circular convolution................. 67 2.7.4 Fast Fourier transform ..................................... 69 2.8 Exercises........................................................... 70 3. Discrete Wavelet Transforms 73 3.1 Overview ........................................................... 73 3.2 Haar Wavelet Transform for Digital Signals.......................... 74 3.2.1 Basic example............................................... 74 3.2.2 Prediction and update transformations....................... 77 3.3 Multiple Scale Haar Wavelet Transform............................... 80 3.3.1 Matrix description of multiresolution representation .... 80 3.3.2 Signal processing using the multiresolution representation . 83 3.4 Wavelet Transforms for Periodic Signals by Lifting.................. 85 3.4.1 CDF(2,2) transform.......................................... 85 3.4.2 Daub4 transform............................................. 89 3.5 Wavelet Bases for Periodic Signals.................................. 93 3.5.1 Lifting steps and polyphase matrices........................ 93 3.5.2 One-scale wavelet matrices.................................. 97 3.5.3 Trend and detail subspaces..................................101 3.5.4 Multiscale wavelet matrices.................................104 3.6 Two-Dimensional Wavelet Transforms..................................Ill 3.6.1 Images as matrices..........................................Ill 3.6.2 One-scale 2D wavelet transform..............................112 3.6.3 Multiscale 2D wavelet transform.............................116 3.6.4 Image compression using wavelet transforms..................118 3.7 Computer Explorations...............................................120 3.7.1 Haar transform..............................................120 3.7.2 CDF(2, 2) wavelet transform.................................122 3.7.3 Daub4 wavelet transform.....................................125 3.7.4 Fast multiscale Haar transform..............................127 3.7.5 Fast multiscale Daub4 transform.............................129 3.7.6 Signal processing with the multiscale Haar transform . . . 131 3.8 Exercises...........................................................135 4. Wavelet Transforms from Filter Banks 141 4.1 Overview . . . .f...................................................141 4.2 Filtering, Downsampling, and Upsampling.............................142 4.2.1 Signals and ¿-transforms....................................143 ր Contents 4.2.2 Convolution ...............................................144 4.2.3 Linear shift-invariant filters.............................146 4.2.4 Downsampling and upsampling................................148 4.2.5 Periodic signals ..........................................150 4.2.6 Filtering and downsampling of periodic signals.............151 4.2.7 Discrete Fourier transform and ¿-transform.................152 4.3 Filter Banks and Polyphase Matrices...............................154 4.3.1 Lazy filter bank...........................................154 4.3.2 Filter banks from lifting..................................156 4.4 Filter Banks and Modulation Matrices..............................159 4.4.1 Lowpass and highpass filters...............................159 4.4.2 Filter banks from filter pairs.............................162 4.4.3 Perfect reconstruction from analysis filters...............166 4.5 Perfect Reconstruction Filter Pairs...............................168 4.5.1 Perfect reconstruction from lowpass filters................168 4.5.2 Lowpass filters and the Bezout polynomials.................169 4.5.3 CDF(p, q) filters..........................................171 4.6 Comparing Polyphase and Modulation Matrices.......................175 4.7 Lifting Step Factorization of Polyphase Matrices..................179 4.8 Biorthogonal Wavelet Bases........................................183 4.9 Orthogonal Filter Banks...........................................187 4.10 Daubechies Wavelet Transforms.....................................191 4.10.1 Power spectral response function...........................191 4.10.2 Construction of the Daub4 filters..........................192 4.10.3 Construction of the Daub2K filters.........................193 4.11 Computer Explorations.............................................194 4.11.1 Signal processing with the CDF(2,2) transform..............195 4.11.2 Two-dimensional discrete wavelet transforms................197 4.11.3 Image compression and multiscale analysis..................199 4.11.4 Fast two-dimensional wavelet transforms....................202 4.11.5 Denoising and compressing images...........................204 4.12 Exercises.........................................................205 5. Wavelet Transforms for Analog Signals , 211 5.1 Overview ....................................................... 211 5.2 Linear Transformations of Analog Signals..........................211 5.2.1 Finite-energy analog signals...............................212 5.2.2 Orthogonal projections.....................................212 5.2.3 Shift and dilation operators...............................214 5.3 Haar Wavelet Transform for Analog Signals.........................215 5.3.1 Haar scaling function......................................215 5.3.2 Haar multiresolution analysis..............................216 Contents xii 5.3.3 Haar wavelet and wavelet transform .......................219 5.4 Scaling and Wavelet Functions from Orthogonal Filter Banks . . . 223 5.4.1 Cascade algorithm.........................................224 5.4.2 Orthogonality relations...................................225 5.5 Multiresolution Analysis of Analog Signals........................233 5.5.1 Multiresolution spaces....................................233 5.5.2 Trend and detail projections..............................235 5.5.3 Fast multiscale wavelet transform.........................239 5.5.4 Vanishing moments for wavelet functions...................241 5.5.5 Guides to wavelet theory and applications.................244 5.6 Computer Explorations.............................................245 5.6.1 Generating scaling and wavelet functions..................245 5.6.2 Using wavelet transforms to find singularities............247 5.7 Exercises.........................................................250 Appendix A Some Mathematical and Software Tools 255 A.l Complex Numbers and Roots of Polynomials .........................255 A.2 Exponential Function and Roots of Unity...........................256 A. 3 Computations in Matlab and Uvi֊Wave ..............................258 A.3.1 Introduction to Matlab....................................258 A.3.2 Uvi„Wave software.........................................260 Appendix B Solutions to Exercises 261 B. l Solutions to Exercises 1.10 261 B.2 Solutions to Exercises 2.8 .......................................265 B.3 Solutions to Exercises 3.8 .......................................268 B.4 Solutions to Exercises 4.12 272 B.5 Solutions to Exercises 5.7........................................280 Bibliography 283 Index 285
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spellingShingle Goodman, Roe 1938-
Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing
aFourier transformationsvTextbooks
aAlgebras, LinearvTextbooks
aSignal processingxMathematicsvTextbooks
aWavelets (Mathematics)vTextbooks
Wavelet-Analyse (DE-588)4760859-6 gnd
Harmonische Analyse (DE-588)4023453-8 gnd
subject_GND (DE-588)4760859-6
(DE-588)4023453-8
title Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing
title_auth Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing
title_exact_search Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing
title_full Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing Roe W. Goodman (Rutgers University, USA)
title_fullStr Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing Roe W. Goodman (Rutgers University, USA)
title_full_unstemmed Discrete Fourier and wavelet transforms an introduction through linear algebra with applications to signal processing Roe W. Goodman (Rutgers University, USA)
title_short Discrete Fourier and wavelet transforms
title_sort discrete fourier and wavelet transforms an introduction through linear algebra with applications to signal processing
title_sub an introduction through linear algebra with applications to signal processing
topic aFourier transformationsvTextbooks
aAlgebras, LinearvTextbooks
aSignal processingxMathematicsvTextbooks
aWavelets (Mathematics)vTextbooks
Wavelet-Analyse (DE-588)4760859-6 gnd
Harmonische Analyse (DE-588)4023453-8 gnd
topic_facet aFourier transformationsvTextbooks
aAlgebras, LinearvTextbooks
aSignal processingxMathematicsvTextbooks
aWavelets (Mathematics)vTextbooks
Wavelet-Analyse
Harmonische Analyse
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