Notes on Digital Signal Processing: Practical Recipes for Design, Analysis and Implementation, Portable Documents

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Notes on Digital Signal Processing: Practical Recipes for Design, Analysis and Implementation, Portable Documents

By C. Britton Rorabaugh
Published Nov 19, 2010 by Pearson.

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Description

Sample Content

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Description

Copyright 2011
Dimensions: 8" x 10"
Edition: 1st

eBook (Watermarked)
ISBN-10: 0-13-259876-0
ISBN-13: 978-0-13-259876-7

The Most Complete, Modern, and Useful Collection of DSP Recipes: More Than 50 Practical Solutions and More than 30 Summaries of Pertinent Mathematical Concepts for Working Engineers

Notes on Digital Signal Processing is a comprehensive, easy-to-use collection of step-by-step procedures for designing and implementing modern DSP solutions. Leading DSP expert and IEEE Signal Processing Magazine associate editor C. Britton Rorabaugh goes far beyond the basic procedures found in other books while providing the supporting explanations and mathematical materials needed for a deeper understanding.

Rorabaugh covers the full spectrum of challenges working engineers are likely to encounter and delves into crucial DSP nuances discussed nowhere else. Readers will find valuable, tested recipes for working with multiple sampling techniques; Fourier analysis and fast Fourier transforms; window functions; classical spectrum analysis; FIR and IIR filter design; analog prototype filters; z-transform analysis; multirate and statistical signal processing; bandpass and quadrature techniques; and much more.

Notes on Digital Signal Processing begins with mapping diagrams that illuminate the relationships between all topics covered in the book. Many recipes include examples demonstrating actual applications, and most sections rely on widely used MATLAB tools.

DSP fundamentals: ideal, natural, and instantaneous sampling; delta functions; physical signal reconstruction; and more
Fourier Analysis: Fourier series and transforms; discrete-time and discrete Fourier transforms; signal truncation; DFT leakage and resolution
Fast Fourier transforms: decimation in time and frequency; prime factor algorithms; and fast convolution
Window techniques: sinusoidal analysis; window characteristics and choices; Kaiser windows; and more
Classical spectrum analysis: unmodified and modified periodograms; Bartlett’s and Welch’s periodograms; and periodogram performance
FIR filters: design options; linear-phase FIR filters; periodicities; basic and Kaiser window methods; and the Parks-McClellan algorithm
Analog prototype filters: Laplace transforms; characterization; and Butterworth, Chebyshev, elliptic, and Bessel filters
z-Transform analysis: computation and transforms using partial fraction expansion
IIR filters: design options; impulse invariance methods; and bilinear transformation
Multirate signal processing: decimation and interpolation fundamentals; multistage and polyphase decimators and interpolation
Bandpass and quadrature techniques: bandpass sampling; wedge diagrams; complex and analytic signals; and advanced signal generation techniques
Statistical signal processing: parametric modeling of discrete-time signals; autoregressive signal models; fitting AR and All-Pole models; and more

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Sample Content

Preface xi

About the Author xiii

Part I: DSP Fundamentals

Note 1: Navigating the DSP Landscape 1-1

Note 2: Overview of Sampling Techniques 2-1

Note 3: Ideal Sampling 3-1

Note 4: Practical Application of Ideal Sampling 4-1

Note 5: Delta Functions and the Sampling Theorem 5-1

Note 6: Natural Sampling 6-1

Note 7: Instantaneous Sampling 7-1

Note 8: Reconstructing Physical Signals 8-1

Part II: Fourier Analysis

Note 9: Overview of Fourier Analysis 9-1

Note 10: Fourier Series 10-1

Note 11: Fourier Transform 11-1

Note 12: Discrete-Time Fourier Transform 12-1

Note 13: Discrete Fourier Transform 13-1

Note 14: Analyzing Signal Truncation 14-1

Note 15: Exploring DFT Leakage 15-1

Note 16: Exploring DFT Resolution 16-1

Part III: Fast Fourier Transform Techniques

Note 17: FFT: Decimation-in-Time Algorithms 17-1

Note 18 FFT: Decimation-in-Frequency Algorithms 18-1

Note 19: FFT: Prime Factor Algorithm 19-1

Note 20: Fast Convolution Using the FFT 20-1

Part IV: Window Techniques

Note 21: Using Window Functions: Some Fundamental Concepts 21-1

Note 22: Assessing Window Functions: Sinusoidal Analysis Techniques 22-1

Note 23: Window Characteristics 23-1

Note 24: Window Choices 24-1

Note 25: Kaiser Windows 25-1

Part V: Classical Spectrum Analysis

Note 26: Unmodified Periodogram 26-1

Note 27: Exploring Periodogram Performance: Sinusoids in Additive White Gaussian Noise 27-1

Note 28: Exploring Periodogram Performance: Modulated Communications Signals 28-1

Note 29: Modified Periodogram 29-1

Note 30: Bartlett’s Periodogram 30-1

Note 31: Welch’s Periodogram 31-1

Part VI: FIR Filter Design

Note 32: Designing FIR Filters: Background and Options 32-1

Note 33: Linear-Phase FIR Filters 33-1

Note 34: Periodicities in Linear-Phase FIR Responses 34-1

Note 35: Designing FIR Filters: Basic Window Method 35-1

Note 36: Designing FIR Filters: Kaiser Window Method 36-1

Note 37: Designing FIR Filters: Parks-McClellan Algorithm 37-1

Part V: Analog Prototype Filters

Note 38: Laplace Transform 38-1

Note 39: Characterizing Analog Filters 39-1

Note 40: Butterworth 40-1

Note 41: Chebyshev Filters 41-1

Note 42: Elliptic Filters 42-1

Note 43: Bessel Filters 43-1

Part VI: z-Transform Analysis

Note 44: The z Transform 44-1

Note 45: Computing the Inverse z Transform Using the Partial Fraction Expansion 45-1

Note 46: Inverse z Transform via Partial Fraction Expansion

Case 1: All Poles Distinct with M < N in System Function 46-1

Note 47: Inverse z Transform via Partial Fraction Expansion

Case 2: All Poles Distinct with M ≥ N in System Function (Explicit Approach) 47-1

Note 48: Inverse z Transform via Partial Fraction Expansion

Case 3: All Poles Distinct with M ≥ N in System Function (Implicit Approach) 48-1

Part VII: IIR Filter Design

Note 49: Designing IIR Filters: Background and Options 49-1

Note 50: Designing IIR Filters: Impulse Invariance Method 50-1

Note 51: Designing IIR Filters: Bilinear Transformation 51-1

Part VIII: Multirate Signal Processing

Note 52: Decimation: The Fundamentals 52-1

Note 53: Multistage Decimators 53-1

Note 54: Polyphase Decimators 54-1

Note 55: Interpolation Fundamentals 55-1

Note 56: Multistage Interpolation 56-1

Note 57: Polyphase Interpolators 57-1

Part IX: Bandpass and Quadrature Techniques

Note 58: Sampling Bandpass Signals 58-1

Note 59: Bandpass Sampling: Wedge Diagrams 59-1

Note 60: Complex and Analytic Signals 60-1

Note 61: Generating Analytic Signals with FIR Hilbert Transformers 61-1

Note 62: Generating Analytic Signals with Frequency-Shifted FIR Lowpass Filters 62-1

Note 63: IIR Phase-Splitting Networks for Generating Analytic Signals 63-1

Note 64: Generating Analytic Signals with Complex Equiripple FIR Filters 64-1

Note 65: Generating I and Q Channels Digitally: Rader’s Approach 65-1

Note 66: Generating I and Q Channels Digitally: Generalization of Rader’s Approach 66-1

Part X: Statistical Signal Processing

Note 67: Parametric Modeling of Discrete-Time Signals 67-1

Note 68: Autoregressive Signal Models 68-1

Note 69: Fitting AR Models to Stochastic Signals: Yule-Walker Method 69-1

Note 70: Fitting All-Pole Models to Deterministic Signals: Autocorrelation Method 70-1

Note 71: Fitting All-Pole Models to Deterministic Signals: Covariance Method 71-1

Note 72: Autoregressive Processes and Linear Prediction Analysis 72-1

Note 73: Estimating Coefficients for Autoregressive Models: Burg Algorithm 73-1

Index I-1

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