Introduction to Orthogonal Transforms
eBook - PDF

Introduction to Orthogonal Transforms

With Applications in Data Processing and Analysis

  1. English
  2. PDF
  3. Available on iOS & Android
eBook - PDF

Introduction to Orthogonal Transforms

With Applications in Data Processing and Analysis

About this book

A systematic, unified treatment of orthogonal transform methods for signal processing, data analysis and communications, this book guides the reader from mathematical theory to problem solving in practice. It examines each transform method in depth, emphasizing the common mathematical principles and essential properties of each method in terms of signal decorrelation and energy compaction. The different forms of Fourier transform, as well as the Laplace, Z-, Walsh–Hadamard, Slant, Haar, Karhunen–Loève and wavelet transforms, are all covered, with discussion of how each transform method can be applied to real-world experimental problems. Numerous practical examples and end-of-chapter problems, supported by online Matlab and C code and an instructor-only solutions manual, make this an ideal resource for students and practitioners alike.

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Yes, you can access Introduction to Orthogonal Transforms by Ruye Wang in PDF and/or ePUB format, as well as other popular books in Technology & Engineering & Signals & Signal Processing. We have over one million books available in our catalogue for you to explore.

Table of contents

  1. Cover
  2. Introduction to Orthogonal Transforms: With Applications in Data Processing and Analysis
  3. Title
  4. Copyright
  5. Dedication
  6. Contents
  7. Preface
  8. Acknowledgments
  9. Notation
  10. 1: Signals and systems
  11. 2: Vector spaces and signal representation
  12. 3: Continuous-time Fourier transform
  13. 4: Discrete-time Fourier transform
  14. 5: Applications of the Fourier transforms
  15. 6: The Laplace and z-transforms
  16. 7: Fourier-related orthogonal transforms
  17. 8: The Walsh-Hadamard, slant, and Haar transforms
  18. 9: Karhunen-Loève transform and principal component analysis
  19. 10: Continuous- and discrete-time wavelet transforms
  20. 11: Multiresolution analysis and discrete wavelet transform
  21. Appendices
  22. Bibliography
  23. Index