Digital Signal Processing, 10th Edition

Digital Signal Processing, 10th Edition

by Maurice Bellanger, Benjamin A. Engel
Released April 2024
Publisher(s): Wiley
ISBN: 9781394182664

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Book description

DIGITAL SIGNAL PROCESSING

Understand the future of signal processing with the latest edition of this groundbreaking text

Signal processing is a key aspect of virtually all engineering fields. Digital techniques enormously expand the possible applications of signal processing, forming a part of not only conventional engineering projects but also data analysis and artificial intelligence. There are considerable challenges raised by these techniques, however, as the gulf between theory and practice can be wide; the successful integration of digital signal processing techniques requires engineers capable of bridging this gulf.

For years, Digital Signal Processing has met this need with a comprehensive guide that consistently connects abstract theory with practical applications. Now fully updated to reflect the most recent developments in this crucial field, the tenth* edition of this seminal text promises to foster a broader understanding of signal processing among a new generation of engineers and researchers.

Readers of the new edition of Digital Signal Processing will also find:

  • Exercises at the end of each chapter to reinforce key concepts
  • A new chapter covering digital signal processing for neural networks
  • Handy structure beginning with undergraduate-level material before moving to more advanced concepts in the second half

Digital Signal Processing is a must-own for students, researchers, and industry professionals in any of the hundreds of fields and subfields that make use of signal processing algorithms.

*This is the English language translation of the French original Traitement Numérique du Signal 10th edition by Maurice Bellanger © Dunod 2022 and is the 4th edition in English.

Table of contents

  1. Cover
  2. Table of Contents
  3. Title Page
  4. Copyright
  5. Foreword (Historical Perspective)
  6. Preface
  7. Introduction
  8. 1 Signal Digitizing – Sampling and Coding
    1. 1.1 Fourier Analysis
    2. 1.2 Distributions
    3. 1.3 Some Commonly Studied Signals
    4. 1.4 The Norms of a Function
    5. 1.5 Sampling
    6. 1.6 Frequency Sampling
    7. 1.7 The Sampling Theorem
    8. 1.8 Sampling of Sinusoidal and Random Signals
    9. 1.9 Quantization
    10. 1.10 The Coding Dynamic Range
    11. 1.11 Nonlinear Coding with the 13-segment A-law
    12. 1.12 Optimal Coding
    13. 1.13 Quantity of Information and Channel Capacity
    14. 1.14 Binary Representations
    15. 1.A Appendix 1: The Function I(x)
    16. 1.B Appendix 2: The Reduced Normal Distribution
    17. Exercises
    18. References
  9. 2 The Discrete Fourier Transform
    1. 2.1 Definition and Properties of the Discrete Fourier Transform
    2. 2.2 Fast Fourier Transform (FFT)
    3. 2.3 Degradation Arising from Wordlength Limitation Effects
    4. 2.4 Calculation of a Spectrum Using the DFT
    5. 2.5 Fast Convolution
    6. 2.6 Calculations of a DFT Using Convolution
    7. 2.7 Implementation
    8. Exercises
    9. References
  10. 3 Other Fast Algorithms for the FFT
    1. 3.1 Kronecker Product of Matrices
    2. 3.2 Factorizing the Matrix of a Decimation-in-Frequency Algorithm
    3. 3.3 Partial Transforms
    4. 3.4 Lapped Transform
    5. 3.5 Other Fast Algorithms
    6. 3.6 Binary Fourier Transform – Hadamard
    7. 3.7 Number-Theoretic Transforms
    8. Exercises
    9. References
  11. 4 Time-Invariant Discrete Linear Systems
    1. 4.1 Definition and Properties
    2. 4.2 The Z-Transform
    3. 4.3 Energy and Power of Discrete Signals
    4. 4.4 Filtering of Random Signals
    5. 4.5 Systems Defined by Difference Equations
    6. 4.6 State Variable Analysis
    7. Exercises
    8. References
  12. 5 Finite Impulse Response (FIR) Filters
    1. 5.1 FIR Filters
    2. 5.2 Practical Transfer Functions and Linear Phase Filters
    3. 5.3 Calculation of Coefficients by Fourier Series Expansion for Frequency Specifications
    4. 5.4 Calculation of Coefficients by the Least-Squares Method
    5. 5.5 Calculation of Coefficient by Discrete Fourier Transform
    6. 5.6 Calculation of Coefficients by Chebyshev Approximation
    7. 5.7 Relationships Between the Number of Coefficients and the Filter Characteristic
    8. 5.8 Raised-Cosine Transition Filter
    9. 5.9 Structures for Implementing FIR Filters
    10. 5.10 Limitation of the Number of Bits for Coefficients
    11. 5.11 Z–Transfer Function of an FIR Filter
    12. 5.12 Minimum-Phase Filters
    13. 5.13 Design of Filters with a Large Number of Coefficients
    14. 5.14 Two-Dimensional FIR Filters
    15. 5.15 Coefficients of Two-Dimensional FIR Filters by the Least-Squares Method
    16. Exercises
    17. References
  13. 6 Infinite Impulse Response (IIR) Filter Sections
    1. 6.1 First-Order Section
    2. 6.2 Purely Recursive Second-Order Section
    3. 6.3 General Second-Order Section
    4. 6.4 Structures for Implementation
    5. 6.5 Coefficient Wordlength Limitation
    6. 6.6 Internal Data Wordlength Limitation
    7. 6.7 Stability and Limit Cycles
    8. Exercises
    9. References
  14. 7 Infinite Impulse Response Filters
    1. 7.1 General Expressions for the Properties of IIR Filters
    2. 7.2 Direct Calculations of the Coefficients Using Model Functions
    3. Exercises
    4. References
  15. 8 Digital Ladder Filters
    1. 8.1 Properties of Two-Port Circuits
    2. 8.2 Simulated Ladder Filters
    3. 8.3 Switched-Capacitor Filters
    4. 8.4 Lattice Filters
    5. 8.5 Comparison Elements
    6. Exercises
    7. References
  16. 9 Complex Signals – Quadrature Filters – Interpolators
    1. 9.1 The Fourier Transform of a Real and Causal Set
    2. 9.2 Analytic Signals
    3. 9.3 Calculating the Coefficients of an FIR Quadrature Filter
    4. 9.4 Recursive 90° Phase Shifters
    5. 9.5 Single Side-Band Modulation
    6. 9.6 Minimum-Phase Filters
    7. 9.7 Differentiator
    8. 9.8 Interpolation Using FIR Filters
    9. 9.9 Lagrange Interpolation
    10. 9.10 Interpolation by Blocks – Splines
    11. 9.11 Interpolations and Signal Restoration
    12. 9.12 Conclusion
    13. Exercises
    14. References
  17. 10 Multirate Filtering
    1. 10.1 Decimation and Z-Transform
    2. 10.2 Decomposition of a Low-Pass FIR Filter
    3. 10.3 Half-Band FIR Filters
    4. 10.4 Decomposition with Half-Band Filters
    5. 10.5 Digital Filtering by Polyphase Network
    6. 10.6 Multirate Filtering with IIR Elements
    7. 10.7 Filter Banks Using Polyphase Networks and DFT
    8. 10.8 Conclusion
    9. Exercises
    10. References
  18. 11 QMF Filters and Wavelets
    1. 11.1 Decomposition into Two Sub-Bands and Reconstruction
    2. 11.2 QMF Filters
    3. 11.3 Perfect Decomposition and Reconstruction
    4. 11.4 Wavelets
    5. 11.5 Lattice Structures
    6. Exercises
    7. References
  19. 12 Filter Banks
    1. 12.1 Decomposition and Reconstruction
    2. 12.2 Analyzing the Elements of the Polyphase Network
    3. 12.3 Determining the Inverse Functions
    4. 12.4 Banks of Pseudo-QMF Filters
    5. 12.5 Determining the Coefficients of the Prototype Filter
    6. 12.6 Realizing a Bank of Real Filters
    7. Exercises
    8. References
  20. 13 Signal Analysis and Modeling
    1. 13.1 Autocorrelation and Intercorrelation
    2. 13.2 Correlogram Spectral Analysis
    3. 13.3 Single-Frequency Estimation
    4. 13.4 Correlation Matrix
    5. 13.5 Modeling
    6. 13.6 Linear Prediction
    7. 13.7 Predictor Structures
    8. 13.8 Multiple Sources – MIMO
    9. 13.9 Conclusion
    10. Appendix: Estimation Bounds
    11. Exercises
    12. References
  21. 14 Adaptive Filtering
    1. 14.1 Principle of Adaptive Filtering
    2. 14.2 Convergence Conditions
    3. 14.3 Time Constant
    4. 14.4 Residual Error
    5. 14.5 Complexity Parameters
    6. 14.6 Normalized Algorithms and Sign Algorithms
    7. 14.7 Adaptive FIR Filtering in Cascade Form
    8. 14.8 Adaptive IIR Filtering
    9. 14.9 Conclusion
    10. Exercises
    11. References
  22. 15 Neural Networks
    1. 15.1 Classification
    2. 15.2 Multilayer Perceptron
    3. 15.3 The Backpropagation Algorithm
    4. 15.4 Examples of Application
    5. 15.5 Convolution Neural Networks
    6. 15.6 Recurrent/Recursive Neural Networks
    7. 15.7 Neural Network and Signal Processing
    8. 15.8 On Activation Functions
    9. 15.9 Conclusion
    10. Exercises
    11. References
  23. 16 Error-Correcting Codes
    1. 16.1 Reed–Solomon Codes
    2. 16.2 Convolutional Codes
    3. 16.3 Conclusion
    4. Exercises
    5. References
  24. 17 Applications
    1. 17.1 Frequency Detection
    2. 17.2 Phase-locked Loop
    3. 17.3 Differential Coding of Speech
    4. 17.4 Coding of Sound
    5. 17.5 Echo Cancelation
    6. 17.6 Television Image Processing
    7. 17.7 Multicarrier Transmission – OFDM
    8. 17.8 Mobile Radiocommunications
    9. References
  25. Exercises: Solutions and Hints
    1. Chapter 1
    2. Chapter 2
    3. Chapter 3
    4. Chapter 4
    5. Chapter 5
    6. Chapter 6
    7. Chapter 7
    8. Chapter 8
    9. Chapter 9
    10. Chapter 10
    11. Chapter 11
    12. Chapter 12
    13. Chapter 13
    14. Chapter 14
    15. Chapter 15
    16. Chapter 16
  26. Index
  27. End User License Agreement

Product information

  • Title: Digital Signal Processing, 10th Edition
  • Author(s): Maurice Bellanger, Benjamin A. Engel
  • Release date: April 2024
  • Publisher(s): Wiley
  • ISBN: 9781394182664