Alexander D. Poularikas
Understanding Digital Signal Processing with MATLAB® and Solutions
Paperback Engels 2021 9780367779122Levertijd ± 8 werkdagen
Gratis verzonden
Samenvatting
The book discusses receiving signals that most electrical engineers detect and study. The vast majority of signals could never be detected due to random additive signals, known as noise, that distorts them or completely overshadows them. Such examples include an audio signal of the pilot communicating with the ground over the engine noise or a bioengineer listening for a fetus’ heartbeat over the mother’s. The text presents the methods for extracting the desired signals from the noise. Each new development includes examples and exercises that use MATLAB to provide the answer in graphic forms for the reader's comprehension and understanding.
Specificaties
ISBN13:9780367779122
Taal:Engels
Bindwijze:Paperback
Aantal pagina's:472
Uitgever:Taylor & Francis Ltd
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Inhoudsopgave
Abbreviations
Chapter 1 Continuous and Discrete Signals
Chapter 2 Fourier Analysis of Continuous and Discrete Signals
Chapter 3 The z-Transform, Difference Equations, and Discrete Systems
Chapter 4 Finite Impulse Response (FIR) Digital Filter Design
Chapter 5 Random Variables, Sequences, and Probability Functions
Chapter 6 Linear Systems with Random Inputs, Filtering, and Power Spectral Density
Chapter 7 Least Squares-Optimum Filtering
Chapter 8 Nonparametric (Classical) Spectra Estimation
Chapter 9 Parametric and Other Methods for Spectra Estimation
Chapter 10 Newton’s and Steepest Descent Methods
Chapter 11 The Least Mean Square (LMS) Algorithm
Chapter 12 Variants of Least Mean Square Algorithm
Chapter 13 Nonlinear Filtering
Appendix 1: Suggestions and Explanations for MATLAB Use
Appendix 2: Matrix Analysis
Appendix 3: Mathematical Formulas
Appendix 4: MATLAB Function Bibliography
Index
Chapter 1 Continuous and Discrete Signals
Chapter 2 Fourier Analysis of Continuous and Discrete Signals
Chapter 3 The z-Transform, Difference Equations, and Discrete Systems
Chapter 4 Finite Impulse Response (FIR) Digital Filter Design
Chapter 5 Random Variables, Sequences, and Probability Functions
Chapter 6 Linear Systems with Random Inputs, Filtering, and Power Spectral Density
Chapter 7 Least Squares-Optimum Filtering
Chapter 8 Nonparametric (Classical) Spectra Estimation
Chapter 9 Parametric and Other Methods for Spectra Estimation
Chapter 10 Newton’s and Steepest Descent Methods
Chapter 11 The Least Mean Square (LMS) Algorithm
Chapter 12 Variants of Least Mean Square Algorithm
Chapter 13 Nonlinear Filtering
Appendix 1: Suggestions and Explanations for MATLAB Use
Appendix 2: Matrix Analysis
Appendix 3: Mathematical Formulas
Appendix 4: MATLAB Function Bibliography
Index
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