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Introduction to Orthogonal Transforms
With Applications in Data Processing and Analysis


  • Author: Ruye Wang, Harvey Mudd College, California
  • Date Published: March 2012
  • availability: In stock
  • format: Hardback
  • isbn: 9780521516884

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About the Authors
  • 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.

    • Discusses the actual computational implementations as well as the theoretical background of various orthogonal transform methods
    • Emphasizes the importance of hands-on skills and problem-solving capabilities with numerous end-of-chapter problems and practical examples
    • Supplementary materials are provided online, including Matlab and C code segments and a solutions manual
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    Product details

    • Date Published: March 2012
    • format: Hardback
    • isbn: 9780521516884
    • length: 590 pages
    • dimensions: 252 x 179 x 30 mm
    • weight: 1.29kg
    • contains: 191 b/w illus. 5 tables 117 exercises
    • availability: In stock
  • Table of Contents

    1. Signals and systems
    2. Vector spaces and signal representation
    3. Continuous-time Fourier transform
    4. Discrete-time Fourier transform
    5. Applications of the Fourier transforms
    6. The Laplace and z-transforms
    7. Fourier related orthogonal transforms
    8. The Walsh–Hadamard, slant and Haar transforms
    9. Karhunen–Loeve transform and principal component analysis
    10. Continuous and discrete-time wavelet transforms
    11. Multiresolution analysis and discrete wavelet transform
    Appendix 1. Review of linear algebra
    Appendix 2. Review of random variables.

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    Introduction to Orthogonal Transforms

    Ruye Wang

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  • Author

    Ruye Wang, Harvey Mudd College, California
    Ruye Wang is a Professor in the Engineering Department at Harvey Mudd College. Previously a Principal Investigator at the Jet Propulsion Laboratory, NASA, his research interests include image processing, computer vision, machine learning and remote sensing.

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