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E-raamat: Digital Audio Signal Processing

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  • Formaat: EPUB+DRM
  • Ilmumisaeg: 24-Feb-2022
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119832690
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Digital Audio Signal ProcessingSuurem pilt
  • Formaat: EPUB+DRM
  • Ilmumisaeg: 24-Feb-2022
  • Kirjastus: John Wiley & Sons Inc
  • Keel: eng
  • ISBN-13: 9781119832690
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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.
Preface for the Third Edition viii
Preface for the Second Edition ix
Preface for the First Edition x
1 Introduction
1(24)
U. Zolzer
1.1 Continuous-time Signals and Convolution
1(5)
1.2 Continuous-time Fourier Transform and Laplace Transform
6(1)
1.3 Sampling and Reconstruction
6(2)
1.4 Discrete-time Signals and Convolution
8(3)
1.5 Discrete-time Fourier Transform and Z-Transform
11(1)
1.6 Discrete Fourier Transform
11(1)
1.7 FIR and IIR Filters
12(6)
1.8 Adaptive Filters
18(3)
1.9 Exercises
21(2)
References
23(2)
2 Quantization
25(42)
U. Zolzer
2.1 Signal Quantization
25(15)
2.1.1 Classical Quantization Model
25(3)
2.1.2 Quantization Theorem
28(6)
2.1.3 Statistics of Quantization Error
34(6)
2.2 Dither
40(6)
2.2.1 Basics
40(4)
2.2.2 Implementation
44(1)
2.2.3 Examples
44(2)
2.3 Spectrum Shaping of Quantization - Noise Shaping
46(5)
2.4 Number Representation
51(11)
2.4.1 Fixed-point Number Representation
52(5)
2.4.2 Floating-point Number Representation
57(3)
2.4.3 Effects on Format Conversion and Algorithms
60(2)
2.5 JS Applet -- Quantization, Dither, and Noise Shaping
62(2)
2.6 Exercises
64(1)
References
65(2)
3 Sampling Rate Conversion
67(30)
U. Zolzer
3.1 Basics
67(3)
3.1.1 Upsampling and Anti-Imaging Filtering
68(1)
3.1.2 Downsampling and Antialiasing Filtering
69(1)
3.2 Synchronous Conversion
70(4)
3.3 Asynchronous Conversion
74(9)
3.3.1 Single-stage Methods
76(2)
3.3.2 Multistage Methods
78(2)
3.3.3 Control of Interpolation Filters
80(3)
3.4 Interpolation Methods
83(11)
3.4.1 Polynomial Interpolation
83(2)
3.4.2 Lagrange Interpolation
85(2)
3.4.3 Spline Interpolation
87(7)
3.5 Exercises
94(1)
References
95(2)
4 AD/DA Conversion
97(34)
U. Zolzer
4.1 Methods
97(16)
4.1.1 Nyquist Sampling
97(1)
4.1.2 Oversampling
98(2)
4.1.3 Delta-sigma Modulation
100(13)
4.2 AD Converters
113(7)
4.2.1 Specifications
113(3)
4.2.2 Parallel Converter
116(1)
4.2.3 Successive Approximation
117(1)
4.2.4 Counter Methods
118(2)
4.2.5 Delta-sigma AD Converter
120(1)
4.3 DA Converters
120(7)
4.3.1 Specifications
121(2)
4.3.2 Switched Voltage and Current Sources
123(1)
4.3.3 Weighted Resistors and Capacitors
124(2)
4.3.4 R-2R Resistor Networks
126(1)
4.3.5 Delta-sigma DA Converter
127(1)
4.4 JS Applet -- Oversampling and Quantization
127(2)
4.5 Exercises
129(1)
References
130(1)
5 Audio Processing Systems
131(18)
U. Zolzer
D. Ahlers
5.1 Digital Signal Processors
132(1)
5.1.1 Fixed-point DSPs
132(1)
5.1.2 Floating-point DSPs
133(1)
5.2 Digital Audio Interfaces
133(13)
5.2.1 Two-channel AES/EBU Interface
134(1)
5.2.2 MADI Interface
135(4)
5.2.3 Audio in HDMI
139(1)
5.2.4 Audio Computer Interfaces
140(1)
5.2.5 Audio Network Interfaces
141(5)
5.3 Two-channel Systems
146(1)
5.4 Multi-channel Systems
146(1)
References
147(2)
6 Equalizers
149(76)
U. Zolzer
6.1 Basics
149(4)
6.2 Recursive Audio Filters
153(37)
6.2.1 Design
153(9)
6.2.2 Parametric Filter Structures
162(10)
6.2.3 Quantization Effects
172(18)
6.3 Non-recursive Audio Filters
190(12)
6.3.1 Basics of Fast Convolution
191(3)
6.3.2 Fast Convolution of Long Sequences
194(7)
6.3.3 Filter Design by Frequency Sampling
201(1)
6.4 Multi-complementary Filter Bank
202(12)
6.4.1 Principles
203(5)
6.4.2 Example: Eight-band Multi-complementary Filter Bank
208(6)
6.5 Delay-based Audio Effects
214(1)
6.6 JS Applet -- Audio Filters
215(2)
6.7 Exercises
217(3)
References
220(5)
7 Room Simulation
225(40)
U. Zolzer
P. Nowak
P. Bhattacharya
7.1 Basics
225(10)
7.1.1 Room Acoustics
225(2)
7.1.2 Model-based Room Impulse Responses
227(3)
7.1.3 Measurement of Room Impulse Responses
230(4)
7.1.4 Simulation of Room Impulse Responses
234(1)
7.2 Early Reflections
235(6)
7.2.1 Ando's Investigations
235(1)
7.2.2 Gerzon Algorithm
236(5)
7.3 Subsequent Reverberation
241(15)
7.3.1 Schroeder Algorithm
241(8)
7.3.2 General Feedback Systems
249(3)
7.3.3 Feedback Allpass Systems
252(4)
7.4 Approximation of Room Impulse Responses
256(2)
7.5 JS Applet -- Fast Convolution
258(1)
7.6 Exercises
259(1)
References
260(5)
8 Dynamic Range Control
265(26)
U. Zolzer
E. Gerat
8.1 Basics
265(1)
8.2 Static Curve
266(3)
8.3 Dynamic Behavior
269(4)
8.3.1 Level Measurement
269(3)
8.3.2 Gain Factor Smoothing
272(1)
8.3.3 Time Constants
272(1)
8.4 Implementation
273(5)
8.4.1 Limiter
273(1)
8.4.2 Compressor
274(2)
8.4.3 Compressor, Expander, Noise Gate
276(1)
8.4.4 Combination System
276(2)
8.5 Realization Aspects
278(2)
8.5.1 Sampling Rate Reduction
278(1)
8.5.2 Curve Approximation
279(1)
8.5.3 Stereo Processing
280(1)
8.6 Multiband DRC
280(1)
8.7 Dynamic Equalizers
281(2)
8.8 Source-filter DRC
283(4)
8.8.1 Introduction
283(1)
8.8.2 Combination with DRC
284(1)
8.8.3 Applications
284(3)
8.9 JS Applet -- Dynamic Range Control
287(1)
8.10 Exercises
288(1)
References
289(2)
9 Audio Coding
291(50)
U. Zolzer
P. Bhattacharya
9.1 Lossless Audio Coding
291(2)
9.2 Lossy Audio Coding
293(2)
9.3 Psychoacoustics
295(8)
9.3.1 Critical Bands and Absolute Threshold
295(2)
9.3.2 Masking
297(6)
9.4 ISO-MPEG1 Audio Coding
303(7)
9.4.1 Filter Banks
303(2)
9.4.2 Psychoacoustic Models
305(4)
9.4.3 Dynamic Bit Allocation and Coding
309(1)
9.5 MPEG-2 Audio Coding
310(1)
9.6 MPEG-2 Advanced Audio Coding
310(11)
9.7 MPEG-4 Audio Coding
321(4)
9.8 Spectral Band Replication
325(2)
9.9 Constrained Energy Lapped Transform -- Gain and Shape Coding
327(6)
9.9.1 Gain Quantization
329(1)
9.9.2 Shape Quantization
330(1)
9.9.3 Range Coding
331(1)
9.9.4 CELT Decoding
332(1)
9.10 JS Applet -- Psychoacoustics
333(1)
9.11 Exercises
333(1)
References
334(7)
10 Nonlinear Processing
341(26)
M. Holters
L. Koper
10.1 Fundamentals
341(2)
10.2 Overdrive, Distortion, Clipping
343(4)
10.3 Nonlinear Filters
347(3)
10.4 Aliasing and its Mitigation
350(4)
10.5 Virtual Analog Modeling
354(9)
10.5.1 Wave Digital Filters
355(4)
10.5.2 State-space Approaches
359(4)
10.6 Exercises
363(1)
References
364(3)
11 Machine Learning for Audio
367(34)
P. Bhattaeharya
P. Nowak
U. Zolzer
11.1 Introduction
367(1)
11.2 Unsupervised and Supervised Learning
368(1)
11.3 Gradient Descent and Backpropagation
369(6)
11.3.1 Feedforward Artificial Neural Network
369(4)
11.3.2 Convolutional Neural Network
373(2)
11.4 Applications
375(19)
11.4.1 Parametric Filter Adaptation
375(8)
11.4.2 Room Simulation
383(5)
11.4.3 Audio Denoising
388(6)
11.5 Exercises
394(1)
References
394(7)
Index 401
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.
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