Sampling Theory in Fourier and Signal Analysis Volume 2 Advanced Topics [Hardcover]

The second in a two-volume series on signal analysis, this book draws on the foundations laid in the first volume to survey the diverse applications of sampling theory both within mathematics and in other areas of science. Many of the topics included are appearing for the first time in a book, and the book seeks to bring readers to the forefront of research. Topics include combinatorial analysis, number theory, neural networks, derivative sampling, wavelets, stochastic signals, random fields, and abstract harmonic analysis.

List of contributors
1. Applications of sampling theory to combinatorial analysis, stirling numbers, special functions and the Riemann zeta function,P. L. Butzer and M. Hauss
2. Sampling theory and the arithmetic Fourier transform,W. J. Walker
3. Derivative sampling--a paradigm example of multichannel methods,J. R. Higgins
4. Computational methods in linear prediction for band-limited signals based on past samples,D. H. Mugler
5. Interpolation and sampling theories, and linear ordinary boundary value problems,W. N. Everitt and G. Nasri-Roudsari
6. Sampling by generalized kernels,R. L. Stens
7. Sampling theory and wavelets,A. Fischer
8. Approximation by translates of a radial function,N. Dyn
9. Almost sure sampling restoration of band-limited stochastic signals,T. Pog?ny
10. Abstract harmonic analysis and the sampling theorem,M. M. Dodson and M. G. Beaty
References
Author index
Subject index