This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Introduction to Digital Signal Processing is intended primarily as a text for a junior or senior-level course for students of electrical and computer engineering.¿ It is also suitable for self-study by practicing engineers with little or no experience with digital signal processing. Introduction to Digital Signal Processing covers the information that the electrical computing and engineering student needs to know about DSP. Core material, with necessary theory and applications, is presented in Chapters 1-7. Four unique chapters that focus on advanced applications follow the core material. MATLAB® is heavily emphasized throughout the book. Most applications have an accompanying lab or sequence of homework problems that have a lab component.

Table of Contents:
1.1 What is a digital filter? The analog circuit analysis A digital filter replacement 1.2 Overview of Analysis and Design The Analysis Process The Design Process   CHAPTER 2 Discrete-Time Signals 2.0 Introduction 2.1 Discrete-Time Signals and Systems          Unit Impulse and Unit Step Functions       Related operations 2.2 Transformations of Discrete-Time Signals Time Transformations Amplitude Transformations 2.3 Characteristics of Discrete-Time Signals Even and Odd Signals Signals Periodic in n Signals Periodic in & 2.4 Common Discrete-Time Signals 2.5 Discrete-Time Systems 2.6 Convolution for Discrete-Time Systems Impulse representation of discrete-time signals Convolution Properties of convolution Power gain Chapter Summary   CHAPTER 3 Frequency Domain Concepts 3.0 Introduction 3.1 Orthogonal Functions and Fourier Series The Exponential Fourier Series Discrete Fourier Series 3.2 The Fourier Transform Definition of the Fourier Transform Properties of the Fourier Transform Fourier Transforms of Periodic Functions 3.3 The Discrete-Time Fourier Transform The Discrete-Time Fourier Transform (DTFT) Properties of the Discrete-Time Fourier Transform Discrete-Time Fourier Transforms of Periodic Sequences 3.4 Discrete Fourier Transform Shorthand Notation for the DFT Frequency resolution of the DFT 3.5 Fast Fourier Transform Decomposition-in-Time Fast Fourier Transform Algorithm Applications of the Discrete / Fast Fourier Transform Calculation of Fourier Transforms Convolution Calculations with the DFT/FFT Linear Convolution with the DFT Computational Efficiency 3.6 The Laplace Transform Properties of the Laplace transform Transfer functions Frequency response of continuous-time LTI systems 3.7 The z-Transform Definitions of z-Transforms z-Transforms Regions of Convergence Inverse z-Transforms z-Transform Properties LTI System Applications Transfer Functions Causality Stability Invertibility Discrete-Time Fourier Transform–z-transform Relationship Frequency Response Calculation Chapter Summary   Chapter 4 Sampling and Reconstruction       4.1 Sampling Continuous-Time Signals      Impulse Sampling Shannon’s sampling theorem Practical sampling 4.2 Anti-aliasing Filters Low pass analog Butterworth filters A low pass Butterworth analog filter has a transfer function given by Switched-capacitor filters Oversampling 4.3 The Sampling Process Errors in the sampling process 4.4 Analog to Digital Conversion Conversion techniques Successive Approximation Converter Flash Converter Sigma-Delta Conversion Error in A/D conversion process Dither 4.5 Digital to Analog Conversion D/A conversion techniques 4.6 Anti-Imaging Filters     Chapter 5 FIR Filter Design and Analysis   5.1 Filter Specifications 5.2 Fundamentals of FIR Filter Design Linear phase and FIR filters Conditions for linear phase in FIR filters Restrictions Imposed by Symmetry Window Functions and FIR Filters High pass, band pass, and band stop filters 5.3 Advanced Window Functions Kaiser Window Dolph-Chebyshev window 5.4 Frequency Sampling FIR filters 5.5 The Parks-McClellan Design Technique for FIR filters 5.6 Minimum Phase FIR filters 5.7 Applications Moving Average FIR Filter Comb Filters Differentiators Hilbert Transformers 5.8 Summary of FIR Characteristics   Chapter 6 Analysis and Design of IIR Filters 6.1 Fundamental IIR design Using the Bilinear Transform Example 6.1 6.2 Stability of IIR Filters 6.3 Frequency transformations 6.4 Classic IIR filters The Butterworth Filter Chebyshev Filters Inverse Chebyshev filter Elliptic Filters Summary of Classic IIR Filters Invariant Impulse Response 6.5 Poles and Zeros in the z-Plane for IIR Filters Summary of pole and zero locations for IIR filters 6.6 Direct Design of IIR Filters Design by pole/zero placement Design of resonators and notch filters of second order Numerical Direct Design — Pade method Numerical Direct Design — Prony's method Numerical Direct Design — Yule-Walker method 6.7 Applications of IIR Filters All Pass Filters IIR Moving Average Filters IIR Comb Filters Inverse Filters Chapter Summary   Chapter 7 Sample Rate Conversion 7.1 Integer Decimation Frequency spectrum of the down sampled signal Cascaded Decimation 7.2 Integer Interpolation Cascaded Interpolators 7.3 Conversion by a Rational Factor 7.4 FIR Implementation Decimation filters Interpolation filters 7.5 Narrow Band Filters 7.6 Conversion by an Arbitrary Factor Hold interpolation Linear Interpolation 7.7 Bandpass Sampling 7.8 Oversampling in Audio Applications Chapter Summary   Chapter 8 Realization and Implementation of Digital Filters 8.1 Implementation Issues 8.2 Number Representation Two’s Complement Sign/Magnitude Floating point representation 8.3 Realization Structures FIR Structures IIR Structures State Space Representation 8.4 Coefficient Quantization Error 8.5 Output Error due to Input Quantization 8.6 Product Quantization 8.7 Quantization and Dithering 8.8 Overflow and Scaling 8.9 Limit Cycles 8.10 DSP on Microcontrollers Microcontroller Characteristics for DSP Implementation in C FIR Implementation in C IIR Implementation in C Speed optimization   Chapter 9 Digital Audio Signals 9.1 The Nature of Audio Signals 9.2 Audio File Coding Pulse Code Modulation Differential Pulse Code Modulation 9.3 Audio File Formats Lossless file format examples Lossless compressed format examples Lossy compressed format examples 9.4 Audio Effects Oscillators and signal generation Delay Flanging Chorus Tremolo and Vibrato Reverberation The Doppler Effect Equalizers Chapter Summary   Chapter 10 Introduction to Two-Dimensional Digital Signal Processing 10.1 Representation of Two-Dimensional Signals Properties of Two-Dimensional Difference Equations 10.2 Two-Dimensional Transforms The Z-Transform in Two Dimensions The two-dimensional Discrete Fourier Transform Properties of the 2D DFT The Two Dimensional DFT and Convolution The Two-Dimensional DFT and Optics The Discrete Cosine Transform in Two Dimensions 10.3 Two-Dimensional FIR Filters Window method Frequency Sampling in Two-Dimensions Transform methods Applying FIR Filters to Images Chapter Summary     Chapter 11 Introduction to Wavelets 11.1 Overview 11.2 The Short Term Fourier Transform 11.3 Wavelets and the Continuous Wavelet Transform The HAAR Wavelet The Daubechies Wavelet Other Wavelet Families 11.4 Interpretation of the Wavelet Transform Data 11.5 The Undecimated Discrete Wavelet Transform 11.6 The Discrete Wavelet Transform Chapter Summary   APPENDIX A Analog Filter Design A.1 Analog Butterworth Filters A.2 Analog Chebyschev Filters A.3 Analog Inverse Chebyschev Filters A.4 Analog Elliptic Filters A.5 Summary of analog filter characteristics APPENDIX B Bibliography APPENDIX C Background Mathematics C.1. Summation Formulas for Geometric Series C.2. Euler’s Relation C.3.  Inverse Bilateral Z-Transforms by Partial Fraction Expansion C.4. Matrix Algebra C.5 State Variable Equations APPENDIX D MATLAB® User Functions and Commands D.1. MATLAB User Functions D.2. MATLAB Commands