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Digital Signal Processing : a breadth-first approach /

The subject of Digital Signal Processing (DSP) is enormously complex, involving many concepts, probabilities, and signal processing that are woven together in an intricate manner. To cope with this scope and complexity, many DSP texts are often organized around the "numerical examples" of...

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Detalles Bibliográficos
Clasificación:	Libro Electrónico
Autor principal:	Khan, Muhammad N. (Autor)
Otros Autores:	Hasnain, Syed K., Jamil, Mohsin
Formato:	Electrónico eBook
Idioma:	Inglés
Publicado:	Aalborg : River Publishers, 2016.
Colección:	River Publishers series in signal, image and speech processing.
Temas:	Signal processing > Digital techniques. Traitement du signal > Techniques numériques. SCIENCE / Energy TECHNOLOGY / Telecommunications
Acceso en línea:	Texto completo

Tabla de Contenidos:

Front Cover
Half Title Page -Digital Signal Processing: A Breadth
First Approach
River Publishers Series
Title Page
Digital Signal Processing: A Breadth-First Approach
Copyright Page
Contents
Preface
Acknowledgments
List of Figures
List of Tables
List of Abbreviations
Chapter 1
Introduction
1.1 Concept of Signal Processing
1.1.1 Analog Signal Processing
1.1.2 Digital Signal Processing
1.2 Roots of DSP
1.3 Advantages of DSP
1.4 Basic Blocks of Signal Processing System
1.5 DSP Key Operations
1.6 Classification of Signals
1.6.1 Continuous-Time versus Discrete-Time Signals
1.6.2 Continuous-Valued versus Discrete-Valued Signals
1.6.3 Deterministic versus Random Signals
1.6.4 Multi-Channel and Multi-Dimensional Signals
1.7 Application of DSP
1.7.1 Telecommunications
1.7.1.1 Multiplexing
1.7.1.2 Compression
1.7.1.3 Echo control
1.7.2 Audio Signal Processing
1.7.2.1 Speech generation
1.7.2.2 Speech recognition
1.7.3 Echo Location
1.7.3.1 Radar (RAdio Detection And Ranging)
1.7.3.2 Sonar (SOund Navigation And Ranging)
1.7.3.3 Reflection seismology
1.7.4 Image Processing
1.7.4.1 Medical
1.7.4.2 Space
Chapter 2
Signals and Systems (Continuous and Discrete)
2.1 Introduction
2.2 CT Signals
2.2.1 Unit Impulse Function
2.2.2 Step Function
2.2.2.1 Properties of unit step function
2.2.3 Ramp Function
2.2.4 Parabolic Function
2.2.5 Exponential Function
2.2.6 Sinusoidal Function
2.3 Concept of Frequency: Continuous Time Signals
2.3.1 Periodic and Aperiodic Signals
2.4 DT Signals
2.4.1 CT versus DT Signals
2.4.2 Unit Impulse
2.4.3 Unit Step Function
2.4.4 Ramp Function
2.4.5 Parabolic Function
2.4.6 Exponential Function
2.4.7 Sinusoidal Function
2.4.8 Concept of Frequency: DT Signals.
2.5 Time-Domain and Frequency-Domain
2.6 A/D and D/A Conversion
2.6.1 Processing Steps for A/D Conversion
2.6.1.1 Sample and hold
2.6.1.2 Quantization
2.6.1.3 Coding
2.6.2 Sampling of Analog Signals
2.7 The Sampling Theorem
2.8 Quantization Error
2.9 Further about DT Signals
2.9.1 Representing DT Signal
2.9.1.1 Graphical representation (Figure 2.5)
2.9.1.2 Functional representation
2.9.1.3 Sequence representation
2.9.1.4 Tabular representation
2.10 Simple Manipulations
2.10.1 Reflection/Folding/Flipping
2.10.2 Shifting (Advance and Delayed)
2.10.3 Scaling (Time and Magnitude)
2.10.4 Addition and Multiplication
2.10.5 Even and Odd Signals
2.11 Energy and Power Signals
2.12 Systems
2.12.1 DT Systems
2.13 System's Representation
2.13.1 Symbol used for DT Systems
2.13.2 An Adder
2.13.3 A Constant Multiplier
2.13.4 A Signalmultiplier
2.13.5 Unit Delay Element
2.13.6 Unit Advanced Element
2.14 System's Classification
2.14.1 Static versus Dynamic Systems
2.14.2 Time-Invariant versus Time-Variant System
2.14.2.1 Method to workout for time-invariant and time-variant system
2.14.3 Linear versus Non-linear System
2.14.3.1 Linear system
2.14.3.2 Non-linear system
2.14.4 Causal versus Non-Causal System
2.14.5 Stable versus Un-Stable System
2.15 Problems and Solutions
Chapter 3
Convolution and Correlation
3.1 Introduction
3.2 The Convolution Sum
3.3 Properties of Convolution
3.3.1 Commutative Law
3.3.2 Associative Law
3.3.3 Distributive Law
3.4 Application of Convolution
3.4.1
3.4.2
3.5 Methods of Calculating Convolution
3.5.1 Convolution of Delta Function with Delta Function
3.5.2 Convolution of Delta Function with Step Function
3.5.3 Convolution of Step Function with Step Function.
3.5.4 Linear Convolution: Function Format
3.5.5 Linear Convolution: Sequence Format
3.5.5.1 Linear convolution by graphical method
3.5.5.2 Linear convolution by analytical method
3.5.5.3 Linear convolution by matrix method
3.5.5.4 Linear convolution by overlap and add method
3.5.6 Circular Convolution
3.6 Correlation
3.7 Properties of Correlation
3.8 Application of Correlation
3.9 Types of Correlation
3.9.1 Cross-Correlation
3.9.2 Auto-Correlation
3.10 Further Analysis of Cross-Correlation
3.11 Cross-Correlation Coefficient
3.12 Correlation Methods
3.12.1 Correlation by Graphical Method
3.12.2 Correlation by Analytical Method
3.12.3 Correlation by Tabular Shifting Method
3.12.4 Correlation by Convolution Property Method
3.13 Cyclic Correlation
3.14 Further Applications of Correlation
3.15 Problems and Solutions
Chapter 4
Z-Transform
4.1 Introduction
4.2 Z-Transform
4.3 Inverse Z-Transform
4.3.1 Using the Property of Z-Transform
4.3.2 Using the Long Division
4.3.3 Using Residue Method
4.3.3.1 When the poles are real and non-repeated
4.3.3.2 When the poles are real and repeated
4.3.3.3 When the poles are complex
4.4 Theorems and Properties of Z-Transform
4.4.1 Multiplication Property
4.4.2 Linearity Property
4.4.3 Time Shifting Property
4.4.4 Scaling Property
4.4.5 Time Reversal Property
4.4.6 Differentiation Property
4.4.7 Convolution Property
4.4.8 Correlation Property
4.4.9 Initial Value Theorem
4.4.10 Final Value Theorem
4.4.11 Time Delay Property (One-Sided z-Transform)
4.4.12 Time Advance Property
4.5 Problems and Solutions
Chapter 5
Solution of Difference Equation
5.1 Constant-Coefficient Difference Equation
5.2 Solution of Difference Equation
5.2.1 Using Sequential Procedure.
5.2.2 Using Z -Transform
5.2.3 Classical Technique of Difference Equation
5.2.4 The Homogeneous Solution
5.2.4.1 When the auxiliary polynomial roots are real and distinct
5.2.4.2 When the characteristics polynomial roots are real and repeated
5.2.5 The Particular Solution of Difference Equation
5.2.6 Rules for Choosing Particular Solutions
5.2.6.1 When the forcing function is having term different from the value of the roots of the auxiliary equation
5.2.6.2 When the forcing function is having same term as in the roots of the auxiliary equation
5.2.6.3 When the forcing function is having sinusoidal forcing function
5.3 Problems and Solutions
Chapter 6
Discrete-Time Fourier Transform Discrete Fourier Transform
6.1 Introduction
6.2 Periodic Function and Fourier Synthesis
6.2.1 Constructing aWaveform with SineWaves
6.2.2 Constructing a Waveform with Cosine Waves
6.2.3 Constructing a Waveform with Cosine and Sine Waves
6.2.4 Constructing a Waveform with Sine, Cosine, and a DC
6.2.5 Gibbs' Phenomenon
6.3 Introduction to Fourier Transforms
6.4 DT Fourier Transform
6.5 Properties of the DTFT
6.5.1 Periodicity
6.5.2 Linearity
6.5.3 Time Shifting
6.5.4 Frequency Shifting
6.5.5 Scaling
6.5.6 Multiplication by n (Frequency Differentiation)
6.5.7 Time Reversal
6.5.8 Convolution
6.5.9 Multiplication in Time Domain
6.5.10 Complex Conjugation and Conjugate Symmetry
6.5.11 Parseval's Theorem
6.5.12 Energy Density Spectrum
6.6 Why the DFT?
6.6.1 Window
6.6.2 Orthogonal Signals
6.6.3 Inside the DFT
6.6.4 DFT Frequencies and Frequency Resolution
6.6.4.1 Spectral leakage due to correlation
6.6.4.2 Spectral leakage due to discontinuities
6.7 Discrete Fourier Transform
6.7.1 Inverse Discrete Fourier Transform
6.7.2 DFT: Matrix Method.
6.7.3 IDFT: Matrix Method
6.8 Properties of the DFT
6.8.1 Periodicity
6.8.2 Linearity
6.8.3 Time Reversal
6.8.4 Circular Time Shift
6.8.5 Circular Frequency Shift
6.8.6 Circular Convolution
6.8.7 Circular Correlation
6.8.8 Multiplication of Two Sequences
6.8.9 Even Functions
6.8.10 Odd Functions
6.8.11 Parseval's Theorem
6.9 Comparison between DTFT and DFT
6.10 Fast Fourier Transform
6.10.1 Decomposition-in-Time (DIT) FFT Algorithm
6.10.1.1 Two-point FFT
6.10.1.2 Four-point FFT
6.10.1.3 Eight-point FFT
6.11 Decomposition-in-Frequency (DIF) FFT Algorithm
6.11.1 Two-point DFT
6.11.2 Four-point DFT
6.12 Problems and Solutions
Chapter 7- Structure for FIR and IIR Filters
7.1 Introduction
7.2 Structure Form of FIR Filters
7.2.1 Direct Form (Transversal)
7.2.2 Lattice Structure
7.2.2.1 Direct form filter-to-lattice coefficients
7.2.2.2 Lattice-to-direct form coefficients
7.2.3 Frequency Sampling Form
7.2.4 Fast Convolution Form
7.3 Realization Form of IIR Filters
7.3.1 Direct Form I
7.3.2 Direct Form II
7.3.3 Cascade (Series) Form
7.3.4 Parallel Form
7.3.5 Lattice Structure for IIR Filter
7.3.5.1 Gray-Markel method of IIR lattice structure for ladder coefficients
7.3.5.2 Calculation of ladder coefficients using Gray-Markel method
7.4 Implementation of Filters
7.5 Problems and Solutions
Chapter 8
Introduction to Digital Filters
8.1 Introduction
8.1.1 Types of Filters
8.1.2 Classification of Filters Development Wise
8.1.3 Analog Filters
8.1.4 Types of Analog Filter
8.2 Digital Filters
8.3 Importance and Advantages
8.4 Disadvantages
8.4.1 Speed Limitation
8.4.2 FiniteWord-Length Effects
8.4.3 Limit Cycles
8.4.4 Long Design and Development Times
8.5 Types of Digital Filters.

Digital Signal Processing : a breadth-first approach /

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