Understanding Digital Signal Processing with MATLAB® and Solutions.

✍ Scribed by Poularikas, Alexander D.

• Publisher: CRC Press
• Year: 2017
• Tongue: English
• Leaves: 472
• Edition: First edition.
• Category: Library

✦ Synopsis

"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."--Provided by publisher.  Read more...

✦ Table of Contents

Half Title
Title Page
Copyright Page
Table of Contents
Abbreviations
Author
Chapter 1 Continuous and Discrete Signals
1.1 Continuous Deterministic Signals
Periodic Signals
Non-Periodic Continuous Signals
Unit Step Functions
Ramp Function
Rectangular Function
Triangular Pulse Function
Signum Function
Sinc Function
Gaussian Function
Error Function
Exponential and Double Exponential Functions
Type of Signalsâ#x80
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Even, Odd, Energy and Power
1.2 Sampling of Continuous Signals-Discrete Signals
Table 1.1: Some Useful Functions in Analog and Discrete Forms. Approximation of the Derivative and IntegralImpulse (delta) Function
Table 1.2: Basic Delta Function Properties
The Comb Function
1.3 Signal Conditioning and Manipulation
Modulation
Shifting and Flipping
Time Scaling
Windowing of Signals
Table 1.3: Windows for Continuous Signal Processing
1.4 Convolution of Analog and Discrete Signals
Analog Signals
Discrete Signals
Table 1.4: Basic Convolution Properties
1.5 MATLAB Use for Vectors and Arrays (Matrices)
Examples of Array Operations
Hintsâ#x80
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Suggestionsâ#x80
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Solutions of the Exercises. Chapter 2 Fourier Analysis of Continuous and Discrete Signals2.1 Introduction
2.2 Fourier Transform (FT) of Deterministic Signals
2.3 Sampling of Signals
2.4 Discrete-Time Fourier Transform (DTFT)
2.5 DTFT of Finite-Time Sequences
Windowing
2.6 The Discrete Fourier Transform (DFT)
The Inverse DFT (IDFT)
2.7 Properties of DFT
Linearity
Symmetry
Time Shifting
Frequency Shifting
Time Convolution
Frequency Convolution
Parsevalâ#x80
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s Theorem
2.8 Effect of Sampling Time T
2.9 Effect of Truncation
Windowing
2.10 Resolution
2.11 Discrete Systems. 2.12 Digital Simulation of Analog Systems2.12.1 Second-Order Differential Equations
Hintsâ#x80
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Suggestionsâ#x80
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Solutions of the Exercises
Appendix 2.1: Fourier Transform Properties
Appendix 2.2: Fourier Transform Pairs
Appendix 2.3: DTFT Properties
Appendix 2.4: DFT Properties
Chapter 3 The z-Transform, Difference Equations, and Discrete Systems
3.1 The z-Transform
3.2 Properties of the z-Transform
Table 3.1: Summary of z-Transform Properties
3.3 Inverse z-Transform
Table 3.2: Common z-Transform Pairs
3.4 Transfer Function
Higher-Order Transfer Functions. 3.5 Frequency Response of Discrete Systems3.6 z-Transform Solution of Difference Equations
Hintsâ#x80
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Suggestionsâ#x80
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Solutions of the Exercises
Chapter 4 Finite Impulse Response (FIR) Digital Filter Design
4.1 Introduction
4.2 Finite Impulse Response (FIR) Filters
Discrete Fourier-Series Method
Commonly Used Windows
Discrete Fourier Transform Method
High-Pass Filter
Table 4.1: Frequency Transformations
Hintsâ#x80
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Suggestionsâ#x80
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Solutions of the Exercises
Appendix 4.1: Window Characteristics and Performance
Chapter 5 Random Variables, Sequences, and Probability Functions.

✦ Subjects

Digital Signal Processing;Mathematics & Statistics for Engineers;ENGnetBASE;MATHnetBASE;ElectricalEngineeringnetBASE;SCI-TECHnetBASE;STMnetBASE