Sampling Theory in Fourier and Signal Analysis

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.