Book description
Practical Signals Theory with MATLAB Applications is organized around applications, first introducing the actual behavior of specific signals and then using them to motivate the presentation of mathematical concepts. Tervo sequences the presentation of the major transforms by their complexity: first Fourier, then Laplace, and finally the z-transform.
The goal is to help students who can't visualize phenomena from an equation to develop their intuition and learn to analyze signals by inspection.
Finally, most examples and problems are designed to use MATLAB, making the presentation more in line with modern engineering practice.
Table of contents
- Coverpage
- Titlepage
- Copyright
- Dedication
- Brief Contents
- Contents
- Preface
- Acknowledgments
- 1 Introduction to Signals and Systems
- 2 Classification of Signals
-
3 Linear Systems
- 3.1 Introduction
- 3.2 Definition of a Linear System
- 3.3 Linear System Response Function h(t)
- 3.4 Convolution
- 3.5 Determining h(t) in an Unknown System
- 3.6 Causality
- 3.7 Combined Systems
- 3.8 Convolution and Random Numbers
- 3.9 Useful Hints and Help with MATLAB
- 3.10 Chapter Summary
- 3.11 Conclusions
-
4 The Fourier Series
- Chapter Overview
- 4.1 Introduction
- 4.2 Expressing Signals by Components
- 4.3 Part One—Orthogonal Signals
- 4.4 Orthogonality
- 4.5 Part Two—The Fourier Series
- 4.6 Computing Fourier Series Components
- 4.7 Fundamental Frequency Component
- 4.8 Practical Harmonics
- 4.9 Odd and Even Square Waves
- 4.10 Gibb’s Phenomenon
- 4.11 Setting Up the Fourier Series Calculation
- 4.12 Some Common Fourier Series
- 4.13 Part Three—The Complex Fourier Series
- 4.14 The Complex Fourier Series
- 4.15 Complex Fourier Series Components
- 4.16 Properties of the Complex Fourier Series
- 4.17 Analysis of a DC Power Supply
- 4.18 The Fourier Series with MATLAB
- 4.19 Conclusions
-
5 The Fourier Transform
- 5.1 Introduction
- 5.2 Properties of the Fourier Transform
- 5.3 The Rectangle Signal
- 5.4 The Sinc Function
-
5.5 Signal Manipulations: Time and Frequency
- 5.5.1 Amplitude Variations
- 5.5.2 Stretch and Squeeze: The Sinc Function
- 5.5.3 The Scaling Theorem
- 5.5.4 Testing the Limits
- 5.5.5 A Shift in Time
- 5.5.6 The Shifting Theorem
- 5.5.7 The Fourier Transform of a Shifted Rectangle
- 5.5.8 Impulse Series—The Line Spectrum
- 5.5.9 Shifted Impulse δ(f − f0)
- 5.5.10 Fourier Transform of a Periodic Signal
- 5.6 Fourier Transform Pairs
- 5.7 Rapid Changes vs. High Frequencies
- 5.8 Conclusions
-
6 Practical Fourier Transforms
- 6.1 Introduction
- 6.2 Convolution: Time and Frequency
- 6.3 Transfer Function of a Linear System
- 6.4 Energy in Signals: Parseval’s Theorem for the Fourier Transform
- 6.5 Data Smoothing and the Frequency Domain
- 6.6 Ideal Filters
- 6.7 A Real Lowpass Filter
- 6.8 The Modulation Theorem
- 6.9 Periodic Signals and the Fourier Transform
- 6.10 The Analog Spectrum Analyzer
- 6.11 Conclusions
-
7 The Laplace Transform
- 7.1 Introduction
- 7.2 The Laplace Transform
- 7.3 Exploring the s-Domain
- 7.4 Visualizing the Laplace Transform
- 7.5 Properties of the Laplace Transform
- 7.6 Differential Equations
- 7.7 Laplace Transform Pairs
- 7.8 Circuit Analysis with the Laplace Transform
-
7.9 State Variable Analysis
- 7.9.1 State Variable Analysis—First-Order System
- 7.9.2 First-Order State Space Analysis with MATLAB
- 7.9.3 State Variable Analysis —Second-Order System
- 7.9.4 Matrix Form of the State Space Equations
- 7.9.5 Second-Order State Space Analysis with MATLAB
- 7.9.6 Differential Equation
- 7.9.7 State Space and Transfer Functions with MATLAB
- 7.10 Conclusions
-
8 Discrete Signals
- 8.1 Introduction
- 8.2 Discrete Time vs. Continuous Time Signals
- 8.3 A Discrete Time Signal
-
8.4 Data Collection and Sampling Rate
- 8.4.1 The Selection of a Sampling Rate
- 8.4.2 Bandlimited Signal
- 8.4.3 Theory of Sampling
- 8.4.4 The Sampling Function
- 8.4.5 Recovering a Waveform from Samples
- 8.4.6 A Practical Sampling Signal
- 8.4.7 Minimum Sampling Rate
- 8.4.8 Nyquist Sampling Rate
- 8.4.9 The Nyquist Sampling Rate Is a Theoretical Minimum
- 8.4.10 Sampling Rate and Alias Frequency
- 8.4.11 Practical Aliasing
- 8.4.12 Analysis of Aliasing
- 8.4.13 Anti-Alias Filter
-
8.5 Introduction to Digital Filtering
- 8.5.1 Impulse Response Function
- 8.5.2 A Simple Discrete Response Function
- 8.5.3 Delay Blocks Are a Natural Consequence of Sampling
- 8.5.4 General Digital Filtering
- 8.5.5 The Fourier Transform of Sampled Signals
- 8.5.6 The Discrete Fourier Transform (DFT)
- 8.5.7 A Discrete Fourier Series
- 8.5.8 Computing the Discrete Fourier Transform (DFT)
- 8.5.9 The Fast Fourier Transform (FFT)
- 8.6 Illustrative Examples
- 8.7 Discrete Time Filtering with MATLAB
- 8.8 Conclusions
-
9 The z-Transform
- 9.1 Introduction
- 9.2 The z-Transform
- 9.3 Calculating the z-Transform
- 9.4 A Discrete Time Laplace Transform
- 9.5 Properties of the z-Transform
- 9.6 z-Transform Pairs
- 9.7 Transfer Function of a Discrete Linear System
- 9.8 MATLAB Analysis with the z-Transform
- 9.9 Digital Filtering—FIR Filter
- 9.10 Digital Filtering—IIR Filter
- 9.11 Conclusions
- 10 Introduction to Communications
- A The Illustrated Fourier Transform
- B The Illustrated Laplace Transform
- C The Illustrated z-Transform
- D MATLAB Reference Guide
- E Reference Tables
- Bibliography
- Index
Product information
- Title: Practical Signals Theory with MATLAB Applications
- Author(s):
- Release date: February 2013
- Publisher(s): Wiley
- ISBN: 9781118115398
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