This is the second of a two-volume series on sampling theory. The mathematical foundations were laid in the first volume, and this book surveys the many applications of sampling theory both within mathematics and in other areas of science. Many of the topics covered here are not found in other books, and all are given an up to date treatment bringing the reader's knowledge up to research level. This book consists of ten chapters, written by ten different teams of authors, and the contents range over a wide variety of topics including combinatorial analysis, number theory, neural networks, derivative sampling, wavelets, stochastic signals, random fields, and abstract harmonic analysis. There is a comprehensive, up to date bibliography.
Rezensionen / Stimmen
"In contrast to the first volume, in the present one of the references are given at the end of each chpater. The two indexes, of authors and objects provide an enlarged accessibility to the items included in the book. As to the graphics, it is as beautiful as that of the first volume ... After carefully studying the first volume, the research engineer or applied mathematician can proceed to read this book" Zentralblatt Mathematik
Sprache
Verlagsort
Zielgruppe
Für höhere Schule und Studium
Produkt-Hinweis
Fadenheftung
Gewebe-Einband
Illustrationen
numerous mathematical examples
Maße
Höhe: 234 mm
Breite: 156 mm
Dicke: 21 mm
Gewicht
ISBN-13
978-0-19-853496-9 (9780198534969)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Autor*in
Professor EmeritusProfessor Emeritus, Anglia Polytechnic University, Cambridge
Professor of MathematicsProfessor of Mathematics, Rheinisch-Westfaelische Technische Hochschule, Aachen
1. Applications of sampling theory to combintorial analysis, Stirling numbers, special functions and the Riemann zeta function ; 2. Sampling theory and the arithmetic Fourier transform ; 3. Derivative sampling - a paradigm example of multi-channel methods ; 4. Computational methods in linear prediction for band-limited signals based on past samples ; 5. Interpolation and sampling theories, and linear ordinary boundary value problems ; 6. Sampling by generalized kernels ; 7. Sampling theory and wavelets ; 8. Approximation by translates of a radial function ; 9. Almost sure sampling restoration of band-limited stochastic signals ; 10. Abstract harmonic analysis and the sampling theorem
