Digital Signal Processing : Theory and Practice

Digital Signal Processing Theory and Practice

Detalles Bibliográficos
Autor principal: Bellanger, Maurice (-)
Otros Autores: Engel, Benjamin A.
Formato: Libro electrónico
Idioma:Inglés
Publicado: Newark : John Wiley & Sons, Incorporated 2024.
Edición:10th ed
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009828034706719
Tabla de Contenidos:
  • Cover
  • Title Page
  • Copyright
  • Contents
  • Foreword (Historical Perspective)
  • Preface
  • Introduction
  • Chapter 1 Signal Digitizing - Sampling and Coding
  • 1.1 Fourier Analysis
  • 1.1.1 Fourier Series Expansion of a Periodic Function
  • 1.1.2 Fourier Transform of a Function
  • 1.2 Distributions
  • 1.2.1 Definition
  • 1.2.2 Differentiation of Distributions
  • 1.2.2.1 The Fourier Transform of a Distribution
  • 1.3 Some Commonly Studied Signals
  • 1.3.1 Deterministic Signals
  • 1.3.2 Random Signals
  • 1.3.3 Gaussian Signals
  • 1.3.3.1 Peak Factor of a Random Signal
  • 1.4 The Norms of a Function
  • 1.5 Sampling
  • 1.6 Frequency Sampling
  • 1.7 The Sampling Theorem
  • 1.8 Sampling of Sinusoidal and Random Signals
  • 1.8.1 Sinusoidal Signals
  • 1.8.2 Discrete Random Signals
  • 1.8.3 Discrete Noise Generation
  • 1.9 Quantization
  • 1.10 The Coding Dynamic Range
  • 1.11 Nonlinear Coding with the 13‐segment A‐law
  • 1.12 Optimal Coding
  • 1.13 Quantity of Information and Channel Capacity
  • 1.14 Binary Representations
  • Exercises
  • References
  • Chapter 2 The Discrete Fourier Transform
  • 2.1 Definition and Properties of the Discrete Fourier Transform
  • 2.2 Fast Fourier Transform (FFT)
  • 2.2.1 Decimation‐in‐time Fast Fourier Transform
  • 2.2.2 Decimation‐in‐frequency Fast Fourier Transform
  • 2.2.3 Radix‐4 FFT Algorithm
  • 2.2.4 Split‐radix FFT Algorithm
  • 2.3 Degradation Arising from Wordlength Limitation Effects
  • 2.4 Calculation of a Spectrum Using the DFT
  • 2.4.1 The Filtering Function of the DFT
  • 2.4.2 Spectral Resolution
  • 2.5 Fast Convolution
  • 2.6 Calculations of a DFT Using Convolution
  • 2.7 Implementation
  • Exercises
  • References
  • Chapter 3 Other Fast Algorithms for the FFT
  • 3.1 Kronecker Product of Matrices
  • 3.2 Factorizing the Matrix of a Decimation‐in‐Frequency Algorithm
  • 3.3 Partial Transforms.
  • 3.3.1 Transform of Real Data and Odd DFT
  • 3.3.2 The Odd‐time Odd‐frequency DFT
  • 3.3.3 Sine and Cosine Transforms
  • 3.3.4 The Two‐dimensional DCT
  • 3.4 Lapped Transform
  • 3.5 Other Fast Algorithms
  • 3.6 Binary Fourier Transform - Hadamard
  • 3.7 Number‐Theoretic Transforms
  • Exercises
  • References
  • Chapter 4 Time‐Invariant Discrete Linear Systems
  • 4.1 Definition and Properties
  • 4.2 The Z‐Transform
  • 4.3 Energy and Power of Discrete Signals
  • 4.4 Filtering of Random Signals
  • 4.5 Systems Defined by Difference Equations
  • 4.6 State Variable Analysis
  • Exercises
  • References
  • Chapter 5 Finite Impulse Response (FIR) Filters
  • 5.1 FIR Filters
  • 5.2 Practical Transfer Functions and Linear Phase Filters
  • 5.3 Calculation of Coefficients by Fourier Series Expansion for Frequency Specifications
  • 5.4 Calculation of Coefficients by the Least‐Squares Method
  • 5.5 Calculation of Coefficient by Discrete Fourier Transform
  • 5.6 Calculation of Coefficients by Chebyshev Approximation
  • 5.7 Relationships Between the Number of Coefficients and the Filter Characteristic
  • 5.8 Raised‐Cosine Transition Filter
  • 5.9 Structures for Implementing FIR Filters
  • 5.10 Limitation of the Number of Bits for Coefficients
  • 5.11 Z-Transfer Function of an FIR Filter
  • 5.12 Minimum‐Phase Filters
  • 5.13 Design of Filters with a Large Number of Coefficients
  • 5.14 Two‐Dimensional FIR Filters
  • 5.15 Coefficients of Two‐Dimensional FIR Filters by the Least‐Squares Method
  • Exercises
  • References
  • Chapter 6 Infinite Impulse Response (IIR) Filter Sections
  • 6.1 First‐Order Section
  • 6.2 Purely Recursive Second‐Order Section
  • 6.3 General Second‐Order Section
  • 6.4 Structures for Implementation
  • 6.5 Coefficient Wordlength Limitation
  • 6.6 Internal Data Wordlength Limitation
  • 6.7 Stability and Limit Cycles
  • Exercises
  • References.
  • Chapter 7 Infinite Impulse Response Filters
  • 7.1 General Expressions for the Properties of IIR Filters
  • 7.2 Direct Calculations of the Coefficients Using Model Functions
  • 7.2.1 Impulse Invariance
  • 7.2.2 Bilinear Transform
  • 7.2.2.1 Butterworth Filters
  • 7.2.2.2 Elliptic Filters
  • 7.2.2.3 Calculating any Filter by Transformation of a Low‐pass Filter
  • 7.2.3 Iterative Techniques for Calculating IIR Filter with Frequency
  • 7.2.3.1 Minimizing the Mean Square Error
  • 7.2.3.2 Chebyshev Approximation
  • 7.2.4 Filters Based on Spheroidal Sequences
  • 7.2.5 Structures Representing the Transfer Function
  • 7.2.6 Limiting the Coefficient Wordlength
  • 7.2.7 Round‐Off Noise
  • 7.2.8 Comparison of IIR and FIR Filters
  • Exercises
  • References
  • Chapter 8 Digital Ladder Filters
  • 8.1 Properties of Two‐Port Circuits
  • 8.2 Simulated Ladder Filters
  • 8.3 Switched‐Capacitor Filters
  • 8.4 Lattice Filters
  • 8.5 Comparison Elements
  • Exercises
  • References
  • Chapter 9 Complex Signals - Quadrature Filters - Interpolators
  • 9.1 The Fourier Transform of a Real and Causal Set
  • 9.2 Analytic Signals
  • 9.3 Calculating the Coefficients of an FIR Quadrature Filter
  • 9.4 Recursive 90° Phase Shifters
  • 9.5 Single Side‐Band Modulation
  • 9.6 Minimum‐Phase Filters
  • 9.7 Differentiator
  • 9.8 Interpolation Using FIR Filters
  • 9.9 Lagrange Interpolation
  • 9.10 Interpolation by Blocks - Splines
  • 9.11 Interpolations and Signal Restoration
  • 9.12 Conclusion
  • Exercises
  • References
  • Chapter 10 Multirate Filtering
  • 10.1 Decimation and Z‐Transform
  • 10.2 Decomposition of a Low‐Pass FIR Filter
  • 10.3 Half‐Band FIR Filters
  • 10.4 Decomposition with Half‐Band Filters
  • 10.5 Digital Filtering by Polyphase Network
  • 10.6 Multirate Filtering with IIR Elements
  • 10.7 Filter Banks Using Polyphase Networks and DFT
  • 10.8 Conclusion
  • Exercises.
  • References
  • Chapter 11 QMF Filters and Wavelets
  • 11.1 Decomposition into Two Sub‐Bands and Reconstruction
  • 11.2 QMF Filters
  • 11.3 Perfect Decomposition and Reconstruction
  • 11.4 Wavelets
  • 11.5 Lattice Structures
  • Exercises
  • References
  • Chapter 12 Filter Banks
  • 12.1 Decomposition and Reconstruction
  • 12.2 Analyzing the Elements of the Polyphase Network
  • 12.3 Determining the Inverse Functions
  • 12.4 Banks of Pseudo‐QMF Filters
  • 12.5 Determining the Coefficients of the Prototype Filter
  • 12.6 Realizing a Bank of Real Filters
  • Exercises
  • References
  • Chapter 13 Signal Analysis and Modeling
  • 13.1 Autocorrelation and Intercorrelation
  • 13.2 Correlogram Spectral Analysis
  • 13.3 Single‐Frequency Estimation
  • 13.4 Correlation Matrix
  • 13.5 Modeling
  • 13.6 Linear Prediction
  • 13.7 Predictor Structures
  • 13.7.1 Sensor Networks - Antenna Processing
  • 13.8 Multiple Sources - MIMO
  • 13.9 Conclusion
  • Appendix: Estimation Bounds
  • Exercises
  • References
  • Chapter 14 Adaptive Filtering
  • 14.1 Principle of Adaptive Filtering
  • 14.2 Convergence Conditions
  • 14.3 Time Constant
  • 14.4 Residual Error
  • 14.5 Complexity Parameters
  • 14.6 Normalized Algorithms and Sign Algorithms
  • 14.7 Adaptive FIR Filtering in Cascade Form
  • 14.8 Adaptive IIR Filtering
  • 14.9 Conclusion
  • Exercises
  • References
  • Chapter 15 Neural Networks
  • 15.1 Classification
  • 15.2 Multilayer Perceptron
  • 15.3 The Backpropagation Algorithm
  • 15.4 Examples of Application
  • 15.5 Convolution Neural Networks
  • 15.6 Recurrent/Recursive Neural Networks
  • 15.7 Neural Network and Signal Processing
  • 15.8 On Activation Functions
  • 15.9 Conclusion
  • Exercises
  • References
  • Chapter 16 Error‐Correcting Codes
  • 16.1 Reed-Solomon Codes
  • 16.1.1 Predictable Signals
  • 16.1.2 Reed-Solomon Codes in the Frequency Domain.
  • 16.1.3 Reed-Solomon Codes in the Time Domain
  • 16.1.4 Computing in a Finite Field
  • 16.1.5 Performance of Reed-Solomon Codes
  • 16.2 Convolutional Codes
  • 16.2.1 Channel Capacity
  • 16.2.2 Approaching the Capacity Limit
  • 16.2.3 A Simple Convolutional Code
  • 16.2.4 Coding Gain and Error Probability
  • 16.2.5 Decoding and Output Signals
  • 16.2.6 Recursive Systematic Coding (RSC)
  • 16.2.7 Principle of Turbo Codes
  • 16.2.8 Trellis‐Coded Modulations
  • 16.3 Conclusion
  • Exercises
  • References
  • Chapter 17 Applications
  • 17.1 Frequency Detection
  • 17.2 Phase‐locked Loop
  • 17.3 Differential Coding of Speech
  • 17.4 Coding of Sound
  • 17.5 Echo Cancelation
  • 17.5.1 Data Echo Canceller
  • 17.5.1.1 Two‐wire Line
  • 17.5.2 Acoustic Echo Canceler
  • 17.6 Television Image Processing
  • 17.7 Multicarrier Transmission - OFDM
  • 17.8 Mobile Radiocommunications
  • References
  • Exercises: Solutions and Hints
  • Index
  • EULA.

Ejemplares similares