Subband and Wavelet Transforms

1. Front Matter

   Pages i-xvii

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2. Introduction and Overview

   • Mark J. T. Smith, Ali N. Akansu

   Pages 1-31

3. Fundamentals and Optimal Design of Subband and Wavelet Transforms

   • Ali N. Akansu, Richard A. Haddad

   Pages 33-82

4. Matrix Theory for Filter Bank Analysis and Design

   • Kambiz Nayebi, Thomas P. Barnwell, Mark J. T. Smith

   Pages 83-112

5. IIR Filter Banks and Wavelets

   • Rashid Ansari

   Pages 113-148

6. The Continuous Wavelet Transform, from 1 to 3 Dimensions

   • Jean-Pierre Antoine, Romain Murenzi

   Pages 149-187

7. Time-Frequency Localization with Non-Stationary Wavelet Packets

   • Albert Cohen, Eric Séré

   Pages 189-211

8. Subband Image Coding

   • Bernd Girod, Frank Hartung, Uwe Horn

   Pages 213-250

9. Subband Video Coding

   • Reginald L. Lagendijk, Frank Bosveld, Jan Biemond

   Pages 251-285

10. Audio Coding with Filter Banks

    • James D. Johnston

    Pages 287-307

11. Wavelets and Filter Banks in Spread Spectrum Communication Systems

    • Gary J. Saulnier, Michael J. Medley, Pankaj K. Das

    Pages 309-345

12. Acoustic Echo Cancellation Using Subband Adaptive Filtering

    • Phillip L. De León II, Delores M. Etter

    Pages 347-367

13. Analog Scramblers

    • Richard V. Cox

    Pages 369-389

14. Multitone Modulation

    • Irving Kalet

    Pages 391-412

15. Back Matter

    Pages 413-451

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The scientists and engineers of today are relentless in their continuing study and analysis of the world about us from the microcosm to the macrocosm. A central purpose of this study is to gain sufficient scientific information and insight to enable the development of both representative and useful models of the superabundance of physical processes that surround us. The engineers need these models and the associated insight in order to build the information processing systems and control systems that comprise these new and emerging technologies. Much of the early modeling work that has been done on these systems has been based on the linear time-invariant system theory and its extensive use of Fourier transform theory for both continuous and discrete systems and signals. However many of the signals arising in nature and real systems are neither stationary nor linear but tend to be concentrated in both time and frequency. Hence a new methodology is needed to take these factors properly into account.

• Adaptive Filter
• Modulation
• Scrambler
• analog
• coding
• communication
• filter
• filtering
• filters
• linear optimization
• wavelets

• New Jersey Institute of Technology, USA

  Ali N. Akansu

• Georgia Institute of Technology, USA

  Mark J. T. Smith

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