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Digital Audio Signal Processing
The fully revised new edition of the popular textbook, featuring additional MATLAB exercises and new algorithms for processing digital audio signals
Digital Audio Signal Processing (DASP) techniques are used in a variety of applications, ranging from audio streaming and computer-generated music to real-time signal processing and virtual sound processing.
Digital Audio Signal Processing provides clear and accessible coverage of the fundamental principles and practical applications of digital audio processing and coding. Throughout the book, the authors explain a wide range of basic audio processing techniques and highlight new directions for automatic tuning of different algorithms and discuss state- of-the-art DASP approaches. Now in its third edition, this popular guide is fully updated with the latest signal processing algorithms for audio processing. Entirely new chapters cover nonlinear processing, Machine Learning (ML) for audio applications, distortion, soft/hard clipping, overdrive, equalizers and delay effects, sampling and reconstruction, and more.
Covers the fundamentals of quantization, filters, dynamic range control, room simulation, sampling rate conversion, and audio coding
Describes DASP techniques, their theoretical foundations, and their practical applications
Discusses modern studio technology, digital transmission systems, storage media, and home entertainment audio components
Features a new introductory chapter and extensively revised content throughout
Provides updated application examples and computer-based activities supported with MATLAB exercises and interactive JavaScript applets via an author-hosted companion website
Balancing essential concepts and technological topics, Digital Audio Signal Processing, Third Edition remains the ideal textbook for advanced music technology and engineering students in audio signal processing courses. It is also an invaluable reference for audio engineers, hardware and software developers, and researchers in both academia and industry.
Auteur
Udo Zölzer is Professor of Signal Processing and Communication at Helmut Schmidt University, Hamburg, Germany. His research interests include audio and video signal processing and communications. He is the author of several books including DAFX: Digital Audio Effects.
Résumé
Digital Audio Signal Processing
The fully revised new edition of the popular textbook, featuring additional MATLAB exercises and new algorithms for processing digital audio signals Digital Audio Signal Processing (DASP) techniques are used in a variety of applications, ranging from audio streaming and computer-generated music to real-time signal processing and virtual sound processing. Digital Audio Signal Processing provides clear and accessible coverage of the fundamental principles and practical applications of digital audio processing and coding. Throughout the book, the authors explain a wide range of basic audio processing techniques and highlight new directions for automatic tuning of different algorithms and discuss state- of-the-art DASP approaches. Now in its third edition, this popular guide is fully updated with the latest signal processing algorithms for audio processing. Entirely new chapters cover nonlinear processing, Machine Learning (ML) for audio applications, distortion, soft/hard clipping, overdrive, equalizers and delay effects, sampling and reconstruction, and more.
Contenu
Preface v
1 Introduction 1
*U. Z¨olzer*
1.1 Continuous-time Signals and Convolution 1
1.2 Continuous-time Fourier Transform and Laplace Transform 6
1.3 Sampling and Reconstruction 7
1.4 Discrete-time Signals and Convolution 8
1.5 Discrete-time Fourier Transform and Z-Transform 11
1.6 Discrete Fourier Transform 12
1.7 FIR and IIR Filters 12
1.8 Adaptive Filters 19
1.9 Exercises 22
References 24
2 Quantization 25
*U. Z¨olzer*
2.1 Signal Quantization 25
2.1.1 Classical Quantization Model 25
2.1.2 Quantization Theorem 29
2.1.3 Statistics of Quantization Error 34
2.2 Dither 41
2.2.1 Basics 41
2.2.2 Implementation 44
2.2.3 Examples 45
2.3 Spectrum Shaping of Quantization - Noise Shaping 48
2.4 Number Representation 53
2.4.1 Fixed-point Number Representation 54
2.4.2 Floating-point Number Representation 58
2.4.3 Effects on Format Conversion and Algorithms 62
2.5 JS Applet - Quantization, Dither, and Noise Shaping 64
2.6 Exercises 65
References 67
3 Sampling Rate Conversion 69
*U. Z¨olzer*
3.1 Basics 69
3.1.1 Upsampling and Anti-Imaging Filtering 70
3.1.2 Downsampling and Anti-Aliasing Filtering 71
3.2 Synchronous Conversion 72
3.3 Asynchronous Conversion 75
3.3.1 Single-stage Methods 78
3.3.2 Multistage Methods 80
3.3.3 Control of Interpolation Filters 83
3.4 Interpolation Methods 85
3.4.1 Polynomial Interpolation 85
3.4.2 Lagrange Interpolation 88
3.4.3 Spline Interpolation 89
3.5 Exercises 97
References 98
4 AD/DA Conversion 101
*U. Z¨olzer*
4.1 Methods 101
4.1.1 Nyquist Sampling 101
4.1.2 Oversampling 103
4.1.3 Delta-sigma Modulation 104
4.2 AD Converters 117
4.2.1 Specifications 117
4.2.2 Parallel Converter 120
4.2.3 Successive Approximation 121
4.2.4 Counter Methods 123
4.2.5 Delta-sigma AD Converter 124
4.3 DA Converters 125
4.3.1 Specifications 125
4.3.2 Switched Voltage and Current Sources 127
4.3.3 Weighted Resistors and Capacitors 128
4.3.4 R-2R Resistor Networks 129
4.3.5 Delta-sigma DA Converter 130
4.4 JS Applet - Oversampling and Quantization 131
4.5 Exercises 132
References 133
5 Audio Processing Systems 135
*U. Z¨olzer, D. Ahlers*
5.1 Digital Signal Processors 136
5.1.1 Fixed-point DSPs 136
5.1.2 Floating-point DSPs 137
5.2 Digital Audio Interfaces 138
5.2.1 Two-channel AES/EBU Interface 138
5.2.2 MADI Interface 142
5.2.3 Audio in HDMI 143
5.2.4 Audio Computer Interfaces 145
5.2.5 Audio Network Interfaces 145
5.3 Two-channel Systems 150
5.4 Multi-channel Systems 152
References 152
6 Equalizers 153
*U. Z¨olzer*
6.1 Basics 153
6.2 Recursive Audio Filters 157
6.2.1 Design 157
6.2.2 Parametric Filter Structures 168
6.2.3 Quantization Effects 175
6.3 Nonrecursive Audio Filters 196
6.3.1 Basics of Fast Convolution 196
6.3.2 Fast Convolution of Long Sequences 200
6.3.3 Filter Design by Frequency Sampling 207
6.4 Multi-complementary Filter Bank 208
6.4.1 Principles 209
6.4.2 Example: 8-Band Multi-complementary Filter Bank 214
6.5 Delay-based Audio Effects 220
6.6 JS Applet - Audio Filters 221 6.7 Exercis...