Wavelets with fourier analysis

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Language: English
Cover of the book Wavelets with fourier analysis

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300 p. · 22.9x15.2 cm · Hardback
For courses in Wavelets or Fourier Analysis. This undergraduate text is designed to fill the gap between texts on wavelets that are either too advanced (in terms of mathematical background required) or that contain too little mathematical theory underlying wavelets. It presents most of the theory underlying Fourier analysis and wavelets in a clear and comprehensive fashion--without requiring a graduate background in real analysis.
1. Inner Product Spaces.
2. Fourier Series.
3. The Fourier Transform.
4. Discrete Fourier Analysis.
5. Wavelet Analysis.
6. Multiresolution Analysis.
7. The Daubechies Wavelets.
8. Other Wavelet Topics.
Appendix A. Technical Matters.
Appendix B. MATLAB Routines.
Bibliography.
  • A balance between theory and practical algorithms - e.g., presents the theory surrounding multiresolution analysis (decomposition and reconstruction of wavelet spaces) in a general framework in one section, and the decomposition and reconstruction algorithms in another.
  • Clear presentation of applications to digital signal processing--e.g., data compression, digital filtering and singularity detection.
  • Numerous exercises and examples.
  • Many illustrations.
  • MATLAB code - Includes the code used in many of the algorithms (in the appendix).
  • Emphasis on signal processing.