Applied Signal Processing

by Dutoit, Thierry; Marques, Ferran

• ISBN13: 9780387745343
• ISBN10: 0387745343
• Edition: 1st
• Format: Paperback
• Copyright: 2009-05-04
• Publisher: Springer Nature

Summary

This is a project-oriented laboratory book and CD-ROM focused on digital signal processing (DSP) for students, instructors and professionals. The authors provide eleven large and detailed projects which take the reader through the essentials of signal processing applications. Included are MATLAB codes which are fully commented on for developing working proofs of concepts. The accompanying CD-ROM together with the text directly integrates theory into practice.

Table of Contents

	p. 1
Background - Linear predictive processing of speech	p. 1
The LP model of speech	p. 2
The LP estimation algorithm	p. 4
LP processing in practice	p. 5
Linear predictive coders	p. 7
MATLAB proof of concept: ASP_cell_phone.m	p. 11
Examining a speech file	p. 12
Linear prediction synthesis of 30 ms of voiced speech	p. 13
Linear prediction synthesis of 30 ms of unvoiced speech	p. 18
Linear prediction synthesis of a speech file, with fixed0	p. 19
Unvoiced linear prediction synthesis of a speech file	p. 21
Linear prediction synthesis of speech, with original0	p. 21
CELP analysis-synthesis of a speech file	p. 23
Going further	p. 29
Conclusion	p. 29
References	p. 30
	p. 33
Background - Delta-sigma modulation	p. 34
Uniform quantization: Bits vs. SNR	p. 34
Conventional DACs	p. 36
Oversampling DACs	p. 36
Oversampling DACs - Noise shaping	p. 40
Delta-sigma DACs	p. 42
MATLAB proof of concept: ASP_audio_cd.m	p. 45
Uniform quantization	p. 45
Dithering	p. 47
Conventional DAC	p. 49
Oversampling DAC	p. 53
Oversampling and noise-shaping DAC	p. 57
Delta-sigma DAC	p. 59
Going further	p. 62
Conclusion	p. 62
References	p. 63
	p. 65
Background - Sub-band and transform coding	p. 65
Perfect reconstruction filters	p. 67
Filter banks and lapped transforms	p. 73
Using the masking properties of the human ear	p. 76
Audio coders	p. 77
MATLAB proof of concept: ASP_mp3.m	p. 80
Two-channel filter bank	p. 81
Two-channel QMF filter bank	p. 84
32-channel pseudo-QMF filter bank	p. 86
Filter banks and lapped transforms	p. 89
Perceptual audio coding	p. 92
Going further	p. 100
Conclusion	p. 100
References	p. 101
	p. 103
Background - Statistical pattern recognition	p. 104
The statistical formalism of ASR	p. 105
Markov models	p. 108
Hidden Markov models	p. 111
Training HMMs	p. 115
MATLAB proof of concept: ASP_dictation_machine.m	p. 118
Gaussian modeling and Bayesian classification of vowels	p. 118
Gaussian Mixture Models (GMM)	p. 123
Hidden Markov models (HMM)	p. 134
N-grams	p. 139
Word-based continuous speech recognition	p. 144
Going further	p. 147
Conclusion	p. 147
References	p. 147
	p. 149
Background - The phase vocoder	p. 149
DFT-based signal processing	p. 150
STFT-based signal processing	p. 152
Perfect reconstruction	p. 156
Time scale modification with the phase vocoder	p. 157
Pitch shifting with the phase vocoder	p. 163
MATLAB proof of concept: ASP_audio_effects.m	p. 166
STFT-based audio signal processing	p. 166
Time-scale modification	p. 172
Pitch modification	p. 179
Going further	p. 182
Conclusion	p. 183
References	p. 184
	p. 187
Background - Source localization	p. 188
Sperm whale sounds	p. 188
The Teager-Kaiser energy operator	p. 190
TDOA estimation based on the generalized cross-correlation	p. 192
Adaptive TDOA estimation	p. 195
Multilateration	p. 198
MATLAB proof of concept: ASP_audio_effects.m	p. 199
Sperm whale sounds	p. 199
Teager-Kaiser filtering	p. 203
TDOA estimation using generalized cross-correlation	p. 210
TDOA estimation using least-mean squares	p. 215
Multilateration	p. 218
Going further	p. 220
Conclusion	p. 220
References	p. 221
	p. 223
Background - Audio watermarking seen as a digital communication problem	p. 225
Spread spectrum signals	p. 226
Communication channel design	p. 228
Informed watermarking	p. 233
MATLAB proof of concept: ASP_watermarking.m	p. 238
Audio watermarking seen as a digital communication problem	p. 239
Informed watermarking with error-free detection	p. 244
Informed watermarking made inaudible	p. 247
Informed watermarking robust to MPEG compression	p. 259
Going further	p. 261
Conclusion	p. 262
References	p. 262
	p. 265
Background-JPEG	p. 266
Color transform	p. 268
Frequency transform: The discrete cosine transform	p. 269
Entropy coding	p. 279
A few specificities of the JPEG standard	p. 282
Quality measures	p. 284
MATLAB proof of concept	p. 285
Block image transformation	p. 286
Complete image block coding	p. 293
DCT quantization	p. 295
Spatial decorrelation between blocks	p. 298
Entropy coding	p. 302
Still image coding	p. 306
Going further	p. 308
Conclusions	p. 309
References	p. 309
	p. 311
Background - Motion estimation	p. 312
Motion estimation: The block matching algorithm	p. 316
A few specificities of video coding standards	p. 321
MATLAB proof of concept	p. 325
Macroblock processing	p. 325
Block matching motion estimation	p. 326
Motion compensation	p. 339
Selection of search area	p. 341
Selection of reference image	p. 343
Backward motion estimation	p. 345
Coding of the compensation error	p. 349
Entropy coding	p. 350
Video coding	p. 352
Going further	p. 358
Conclusion	p. 359
References	p. 359
	p. 361
Background - Introduction to wavelet and multi-resolution transforms	p. 365
Think globally, act locally	p. 366
Approximate... but details matter	p. 367
Wavelet transform: Definition and computation	p. 370
WT and discrete signals: DWT	p. 374
WT and DWT for Images: 1+1 = 2	p. 375
Background - Context-based modeling of wavelet coefficients bit planes	p. 376
Spatial and bit-depth scalability	p. 376
Efficient entropy coding	p. 377
Background - Rate-distortion optimal bit allocation across wavelet codeblocks	p. 379
Problem definition	p. 380
Lagrangian formulation and approximated solution	p. 381
Lagrangian optimization: A non-image based example	p. 384
MATLAB proof of concept	p. 386
Experiments with the wavelet transform	p. 387
A simplified JPEG2000 scheme	p. 393
Going further: From concepts to compliant JPEG2000 codestreams	p. 406
Conclusion	p. 408
References	p. 408
	p. 411
Background - Statistical pattern recognition for image classification	p. 414
Statistical framework	p. 415
Gaussian mixture models (GMM)	p. 417
The Expectation-Maximization algorithm (EM)	p. 419
Markov random fields (MRF)	p. 420
Hidden Markov random fields (HMRF)	p. 423
Gaussian hidden Markov random field model	p. 424
MATLAB proof of concept	p. 426
3D data visualization	p. 426
Image histogram	p. 429
Gaussian mixture model (GMM)	p. 431
Hidden Gaussian mixture model	p. 437
Influence of the spatial parameter	p. 439
Localization and quantification of brain degeneration	p. 441
Going further	p. 445
Nature and domain of the transformation	p. 447
Features and cost function	p. 447
Optimization	p. 447
Conclusions	p. 448
Acknowledgments	p. 448
References	p. 449
Index	p. 451
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