Elements of Wavelets for Engineers and Scientists
Elements of Wavelets for Engineers and Scientists is a guide to wavelets for "the rest of us"-practicing engineers and scientists, nonmathematicians who want to understand and apply such tools as fast Fourier and wavelet transforms. It is carefully designed to help professionals in nonmathematical fields comprehend this very mathematically sophisticated topic and be prepared for further study on a more mathematically rigorous level.
Detailed discussions, worked-out examples, drawings, and drill problems provide step-by-step guidance on fundamental concepts such as vector spaces, metric, norm, inner product, basis, dimension, biorthogonality, and matrices.
Chapters explore . . .
* Functions and transforms
* The sampling theorem
* Multirate processing
* The fast Fourier transform
* The wavelet transform
* QMF filters
* Practical wavelets and filters
. . . as well as many new wavelet applications-image compression, turbulence, and pattern recognition, for instance-that have resulted from recent synergies in fields such as quantum physics and seismic geology.
Elements of Wavelets for Engineers and Scientists is a must for every practicing engineer, scientist, computer programmer, and student needing a practical, top-to-bottom grasp of wavelets.
1. Functions and Transforms.
3. Basic and Dimension.
4. Linear Transformations.
5. Sampling Theorem.
6. Multirate Processing.
7. Fast Fourier Transform.
8. Wavelet Transform
9. Quadrature Mirror Filters.
10. Practical Wavelets and Filters.
11. Using Wavelets.
Kraig J. Olejniczak, PhD, PE, is Dean of the College of Engineering at Valparaiso University. He served on the faculty of the University of Arkansas Department of Electrical Energy from 1991 to 2002.
“…(the text is) self-contained and very useful for understanding…” (Zentralblatt Math, Vol.1037, No.12, 2004)
"Elements of Wavelets for Engineers and Scientists is a must for every practicing engineer, scientist, computer programmer, and student needing a practical, top-to-bottom grasp of wavelets.” (Mathmatical Reviews, Issue 2004g)