Digital Signal Processing: A Primer with MATLAB® provides an excellent cover of discrete-time signals and systems.At the beginning of each chapter, an abstract that states the chapter objectives. All principles presented in a lucid, logical, step-by-step approach. As much as possible, the authors avoid wordiness and detail overload that could hide concepts and impede understanding.
In recognition of requirements by the Accreditation Board for Engineering and Technology (ABET) on integrating computer tools, the use of MATLAB® is encouraged in a student-friendly manner. Designed for a three - hours semester course this book is intended as a textbook for a senior-level undergraduate student in electrical and computer engineering.
Author(s): Samir I. Abood
Publisher: CRC Press
Year: 2020
Language: English
Pages: xviii+320
Cover
Half Title
Title Page
Copyright Page
Dedication
Table of Contents
Preface
Acknowledgments
Author
1 Continuous and Discrete Signals
1.1 Continuous Signals
1.1.1 Generation of Continuous Signals in MATLAB
1.1.2 Operations on Signals and Sequences
1.2 Discrete-Time Signals
1.2.1 Complex Sequences
1.3 Signals and Systems
1.4 Classification of Signals and Systems
1.4.1 Continuous-Time and Discrete-Time Signals
1.4.2 Analog and Digital Signals
1.4.3 Deterministic and Random Signals
1.4.4 Periodic and Nonperiodic Signals
1.4.5 Power and Energy Signals
1.4.5.1 What Is Digital Signal Processing
1.4.5.2 Why DSP
1.4.5.3 Applications (DSP
1.5 Introduction to MATLAB in DSP
1.5.1 MATLAB Windows
1.5.2 Basic Commands in MATLAB
1.6 Some Fundamental Sequences
1.6.1 Impulse Response in MATLAB
1.6.2 Signal Duration
1.7 Generation of Discrete Signals in MATLAB
Problems
2 Signals Properties
2.1 Periodic and Aperiodic Sequences
2.2 Even and Odd Parts of a Signal (Symmetric Sequences
2.3 Signal Manipulations
2.3.1 Transformations of the Independent Variable
2.3.1.1 Shifting
2.3.1.2 Reversal
2.3.1.3 Time-Scaling
2.3.1.4 Addition, Multiplication, and Scaling
2.3.1.5 Addition
2.3.1.6 Multiplication
2.3.1.7 Scaling
2.3.1.8 Signal Decomposition
2.4 Discrete-Time Systems
2.4.1 System Properties
2.4.1.1 Memoryless System
2.4.1.2 Additivity
2.4.1.3 Homogeneity
2.4.1.4 Stability
2.5 Linear Time-Invariant Causal Systems (LTI
2.5.1 Linearity
2.5.2 Time-Invariance
2.5.3 Causality
2.6 Definitions
2.6.1 Continuous-Time System
2.6.2 Discrete-Time System
2.6.2.1 Delay Operator
2.6.2.2 Convolution Property
2.6.2.3 Impulse Function
2.6.2.4 Impulse Response
2.6.2.5 Frequency Response
2.7 System Output
2.7.1 Causality
2.7.2 Stability
2.7.3 Invertibility
2.7.4 Memory
Problems
3 Convolution
3.1 Linear Convolution
3.2 Convolution Properties
3.2.1 Commutative Property
3.2.2 Associative Property
3.2.3 Distributive Property
3.3 Types of Convolutions
3.3.1 Equations Method
3.3.1.1 Convolution of Two Sequences in MATLAB
3.3.2 Graphical Method
3.3.3 Tabular Method
Problems
4 Difference Equations
4.1 Difference Equations and Impulse Responses
4.2 System Representation Using Its Impulse Response
4.3 The Methods That One May Use to Solve the Difference Equations
4.4 The Classical Approach
Problems
5 Discrete-Time Fourier Series (DTFS
5.1 DTFS Coefficients of Periodic Discrete Signals
5.2 Parseval’s Relation
5.3 Discreet Fourier Series
Problems
6 Discrete-Time Fourier Transform (DTFT
6.1 Frequency Response
6.2 DTFT for Any Discrete Signal
6.3 Inverse DTFT
6.4 Interconnection of Systems
6.5 DTFT Properties
6.6 Applications of DTFT
6.7 LSI Systems and Difference Equations
6.8 Solving Difference Equations Using DTFT
6.9 Frequency Response in MATLAB
Problems
7 Discrete Fourier Transform (DFT
7.1 Method of Decimation-in-Frequency
7.2 Method of Decimation-in-Time
7.3 Properties of Discrete Fourier Transform
7.4 Discrete Fourier Transform of a Sequence in MATLAB
7.5 Linear Convolution Using the DFT
7.6 Generation of Inverse Discrete Fourier Transform in MATLAB
Problems
8 Fast Fourier Transform (FFT
8.1 Fast Fourier Transform Definition
8.1.1 Decimation-in-Time FFT
8.1.2 Decimation-in-Frequency FFT
8.2 Finding the FFT of Different Signals in MATLAB
8.3 Power Spectral Density Using Square Magnitude and Autocorrelation
8.3.1 Equivalence of FFT and N-phase Sequence Component Transformation
Problems
9 Z-Transform
9.1 Z-Transform Representation
9.2 Region of Convergence (ROC
9.3 Properties of the z-transform
9.4 Inverse z-transform
9.4.1 Partial Fraction Expansion and a Look-up Table
9.4.2 Power Series
9.4.3 Contour Integration
Problems
10 Z-Transform Applications in DSP
10.1 Evaluation of LTI System Response Using Z-Transform
10.2 Digital System Implementation from Its Function
10.3 Pole-Zero Diagrams for a Function in the z-Domain
10.4 Frequency Response Using z-Transform
Problems
11 Pole-Zero Stability
11.1 Concept Poles and Zeros
11.1.1 Stability Determination Based z-Transform
11.1.2 The Z-Transform
11.1.3 The “z-Plane
11.2 Difference Equation and Transfer Function
11.3 BIBO Stability
11.4 The z-Plane Pole-Zero Plot and Stability
11.5 Stability Rules
Problems
12 Sampling
12.1 Relating the FT to the DTFT for Discrete-Time Signals
12.2 Sampling
12.3 Band-Limited Signals
12.4 Sampling of Continuous-Time Signals
12.5 Sampling Theorem
12.6 Band-Pass Sampling
12.7 Quantization
12.8 Uniform and Non-Uniform Quantization
12.9 Audio Sampling
12.10 Sampling Rate
Problems
13 Digital Filters
13.1 Types Of Filters
13.1.1 Low-Pass Filters
13.1.2 High-Pass Filters
13.1.3 Band-Pass Filters
13.1.4 Band-Stop Filters
13.2 Infinite-Impulse-Response (IIR) Digital Filter
13.2.1 Design of Filters Using Bilinear Transformation
13.2.2 Infinite-Impulse Response Filtering
13.2.3 Filter Characteristics
13.3 Finite Impulse Response (FIR) Digital Filter
13.3.1 The Advantages of FIR Filters
13.3.2 FIR Specifications
13.3.3 Gibbs Phenomenon and Different Windowing
13.4 Comparison of IIR and FIR Digital Filters
Problems
14 Implementation of IIR
14.1 Direction-Form I Realization
14.2 Direction-Form II Realization
14.3 Cascade (Series) Realization
14.4 Parallel Realization
14.5 Transposed-Direct-Form-I
14.6 Transposed-Direct-Form-II
14.7 Implementation of a Notch Filter by MATLAB
14.8 Implementation of Infinite-Impulse Response Filters
14.8.1 Analog-to-Digital Filter Design
14.8.2 Bilinear Transformation
Problems
15 Implementation of FIR
15.1 Finite Impulse Response Filter Representation
15.2 Window Method
15.3 FIR-Filter Length Estimation Using Window Functions
Problems
16 Digital Filter Design
16.1 IIR Filter Design
16.1.1 Analog-Filter Design
16.1.2 Bilinear Transformation (IIR Digital Filter
16.1.3 Higher-Order IIR Digital Filters
16.1.4 IIR Digital High-Pass, Band-Pass, and Band-Stop Filter Design
16.1.5 Design a IIR Low-Pass Filter Using MATLAB
16.1.6 Design a IIR High-Pass Filter Using MATLAB
16.1.7 Design an IIR Band-Pass Filter Using MATLAB
16.2 FIR-Filter Design
16.2.1 Design of FIR Filters Using Windows
Problems
Selected Bibliography
Appendix A: Complex Numbers
Appendix B: Mathematical Formulas
Appendix C: MATLAB
Index
