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

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, 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

  • Table of Contents

    1. Title Page
    2. Copyright Page
    3. Dedication Page
    4. Contents
    5. Preface
    6. About the Author
    7. Part I. DSP Fundamentals
      1. Note 1. Navigating the DSP Landscape
      2. Note 2. Overview of Sampling Techniques
      3. Note 3. Ideal Sampling
      4. Note 4. Practical Application of Ideal Sampling
      5. Note 5. Delta Functions and the Sampling Theorem
      6. Note 6. Natural Sampling
      7. Note 7. Instantaneous Sampling
      8. Note 8. Reconstructing Physical Signals
    8. Part II. Fourier Analysis
      1. Note 9. Overview of Fourier Analysis
      2. Note 10. Fourier Series
      3. Note 11. Fourier Transform
      4. Note 12. Discrete-Time Fourier Transform
      5. Note 13. Discrete Fourier Transform
      6. Note 14. Analyzing Signal Truncation
      7. Note 15. Exploring DFT Leakage
      8. Note 16. Exploring DFT Resolution
    9. Part III. Fast Fourier Transform Techniques
      1. Note 17. FFT: Decimation-in-Time Algorithms
      2. Note 18. FFT: Decimation-in-Frequency Algorithms
      3. Note 19. FFT: Prime Factor Algorithm
      4. Note 20. Fast Convolution Using the FFT
    10. Part IV. Window Techniques
      1. Note 21. Using Window Functions: Some Fundamental Concepts
      2. Note 22. Assessing Window Functions: Sinusoidal Analysis Techniques
      3. Note 23. Window Characteristics
      4. Note 24. Window Choices
      5. Note 25. Kaiser Windows
    11. Part V. Classical Spectrum Analysis
      1. Note 26. Unmodified Periodogram
      2. Note 27. Exploring Periodogram Performance: Sinusoids in Additive White Gaussian Noise
      3. Note 28. Exploring Periodogram Performance: Modulated Communications Signals
      4. Note 29. Modified Periodogram
      5. Note 30. Bartlett’s Periodogram
      6. Note 31. Welch’s Periodogram
    12. Part VI. FIR Filter Design
      1. Note 32. Designing FIR Filters: Background and Options
      2. Note 33. Linear-Phase FIR Filters
      3. Note 34. Periodicities in Linear-Phase FIR Responses
      4. Note 35. Designing FIR Filters: Basic Window Method
      5. Note 36. Designing FIR Filters: Kaiser Window Method
      6. Note 37. Designing FIR Filters: Parks-McClellan Algorithm
    13. Part V. Analog Prototype Filters
      1. Note 38. Laplace Transform
      2. Note 39. Characterizing Analog Filters
      3. Note 40. Butterworth Filters
      4. Note 41. Chebyshev Filters
      5. Note 42. Elliptic Filters
      6. Note 43. Bessel Filters
    14. Part VI. z-Transform Analysis
      1. Note 44. The z Transform
      2. Note 45. Computing the Inverse z Transform Using the Partial Fraction Expansion
      3. Note 46. Inverse z Transform via Partial Fraction Expansion: Case 1: All Poles Distinct with M < N in System Function
      4. Note 47. Inverse z Transform via Partial Fraction Expansion: Case 2: All Poles Distinct with M ≥ N in System Function (Explicit Approach)
      5. Note 48. Inverse z Transform via Partial Fraction Expansion: Case 3: All Poles Distinct with M ≥ N in System Function (Implicit Approach)
    15. Part VII. IIR Filter Design
      1. Note 49. Designing IIR Filters: Background and Options
      2. Note 50. Designing IIR Filters: Impulse Invariance Method
      3. Note 51. Designing IIR Filters: Bilinear Transformation
    16. Part VIII. Multirate Signal Processing
      1. Note 52. Decimation: The Fundamentals
      2. Note 53. Multistage Decimators
      3. Note 54. Polyphase Decimators
      4. Note 55. Interpolation Fundamentals
      5. Note 56. Multistage Interpolation
      6. Note 57. Polyphase Interpolators
    17. Part IX. Bandpass and Quadrature Techniques
      1. Note 58. Sampling Bandpass Signals
      2. Note 59. Bandpass Sampling: Wedge Diagrams
      3. Note 60. Complex and Analytic Signals
      4. Note 61. Generating Analytic Signals with FIR Hilbert Transformers
      5. Note 62. Generating Analytic Signals with Frequency-Shifted FIR Lowpass Filters
      6. Note 63. IIR Phase-Splitting Networks for Generating Analytic Signals
      7. Note 64. Generating Analytic Signals with Complex Equiripple FIR Filters
      8. Note 65. Generating I and Q Channels Digitally: Rader’s Approach
      9. Note 66. Generating I and Q Channels Digitally: Generalization of Rader’s Approach
    18. Part X. Statistical Signal Processing
      1. Note 67. Parametric Modeling of Discrete-Time Signals
      2. Note 68. Autoregressive Signal Models
      3. Note 69. Fitting AR Models to Stochastic Signals: The Yule-Walker Method
      4. Note 70. Fitting All-Pole Models to Deterministic Signals: Autocorrelation Method
      5. Note 71. Fitting All-Pole Models to Deterministic Signals: Covariance Method
      6. Note 72. Autoregressive Processes and Linear Prediction Analysis
      7. Note 73. Estimating Coefficients for Autoregressive Models: Burg Algorithm
    19. Index
    20. Footnotes
      1. Chapter 14
      2. Chapter 16
      3. Chapter 23
      4. Chapter 60