
Understanding Digital Signal Processing with MATLAB (R) and Solutions
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"Timely and fundamental subject, sparking interest for students and engineers alike. Starts from the basics and builds up the complexity in a logic and very understandable way, so that both beginners and experienced professionals will be able to profit from the book.The book is very useful as a reference, with an extensive set of digital processing operations and clear MATLAB examples and proposed exercises for all of them. The reader can easily find everything related to one specific topic (eg. Fourier transform)."
- Alexandre Giulietti de Barros, Teledyne Anafocus, Spain
"The book deals with methods for processing noisy signals. The contents is fairly complete and covers all important topics ranging from discrete and continuous Fourier processing, digital filtering to random signal processing and nonlinear filtering."
-Hans-Georg Stark (Aschaffenburg) "Timely and fundamental subject, sparking interest for students and engineers alike. Starts from the basics and builds up the complexity in a logic and very understandable way, so that both beginners and experienced professionals will be able to profit from the book.
The book is very useful as a reference, with an extensive set of digital processing operations and clear MATLAB examples and proposed exercises for all of them. The reader can easily find everything related to one specific topic (eg. Fourier transform)."
- Alexandre Giulietti de Barros, Teledyne Anafocus, Spain
"The book deals with methods for processing noisy signals. The contents is fairly complete and covers all important topics ranging from discrete and continuous Fourier processing, digital filtering to random signal processing and nonlinear filtering."
-Hans-Georg Stark (Aschaffenburg)
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Inhalt
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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