Book description
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, easytouse collection of stepbystep 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; ztransform 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; discretetime 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; linearphase FIR filters; periodicities; basic and Kaiser window methods; and the ParksMcClellan algorithm
Analog prototype filters: Laplace transforms; characterization; and Butterworth, Chebyshev, elliptic, and Bessel filters
zTransform 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 discretetime signals; autoregressive signal models; fitting AR and AllPole models; and more
Table of contents
 Title Page
 Copyright Page
 Dedication Page
 Contents
 Preface
 About the Author
 Part I. DSP Fundamentals
 Part II. Fourier Analysis
 Part III. Fast Fourier Transform Techniques
 Part IV. Window Techniques
 Part V. Classical Spectrum Analysis

Part VI. FIR Filter Design
 Note 32. Designing FIR Filters: Background and Options
 Note 33. LinearPhase FIR Filters
 Note 34. Periodicities in LinearPhase FIR Responses
 Note 35. Designing FIR Filters: Basic Window Method
 Note 36. Designing FIR Filters: Kaiser Window Method
 Note 37. Designing FIR Filters: ParksMcClellan Algorithm
 Part V. Analog Prototype Filters

Part VI. zTransform Analysis
 Note 44. The z Transform
 Note 45. Computing the Inverse z Transform Using the Partial Fraction Expansion
 Note 46. Inverse z Transform via Partial Fraction Expansion: Case 1: All Poles Distinct with M < N in System Function
 Note 47. Inverse z Transform via Partial Fraction Expansion: Case 2: All Poles Distinct with M ≥ N in System Function (Explicit Approach)
 Note 48. Inverse z Transform via Partial Fraction Expansion: Case 3: All Poles Distinct with M ≥ N in System Function (Implicit Approach)
 Part VII. IIR Filter Design
 Part VIII. Multirate Signal Processing

Part IX. Bandpass and Quadrature Techniques
 Note 58. Sampling Bandpass Signals
 Note 59. Bandpass Sampling: Wedge Diagrams
 Note 60. Complex and Analytic Signals
 Note 61. Generating Analytic Signals with FIR Hilbert Transformers
 Note 62. Generating Analytic Signals with FrequencyShifted FIR Lowpass Filters
 Note 63. IIR PhaseSplitting Networks for Generating Analytic Signals
 Note 64. Generating Analytic Signals with Complex Equiripple FIR Filters
 Note 65. Generating I and Q Channels Digitally: Rader’s Approach
 Note 66. Generating I and Q Channels Digitally: Generalization of Rader’s Approach

Part X. Statistical Signal Processing
 Note 67. Parametric Modeling of DiscreteTime Signals
 Note 68. Autoregressive Signal Models
 Note 69. Fitting AR Models to Stochastic Signals: The YuleWalker Method
 Note 70. Fitting AllPole Models to Deterministic Signals: Autocorrelation Method
 Note 71. Fitting AllPole Models to Deterministic Signals: Covariance Method
 Note 72. Autoregressive Processes and Linear Prediction Analysis
 Note 73. Estimating Coefficients for Autoregressive Models: Burg Algorithm
 Index
 Footnotes
Product information
 Title: Notes on Digital Signal Processing: Practical Recipes for Design, Analysis and Implementation
 Author(s):
 Release date: November 2010
 Publisher(s): Pearson
 ISBN: 9780132598804
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