Interpolation, Identification, and Sampling

Jonathan R. Partington

ISBN 10: 0198500246 / ISBN 13: 9780198500247

Published by Oxford University Press, GB, 1997

About this Item

This book is concerned with applications of functional analysis and complex analysis to problems of interpolation in spaces of analytic functions. The problems we look at are those of recovery, producing approximations to functions from measured values. These values may in turn be corrupted by small errors and we wish to be able to produce a good model using this partial and inaccurate information. The practical applications include systems identification, signal processing, and sampling. A selection of the material of this book would be appropriate for a graduate course on function spaces and operators acting on them. Chapter 8 gives a mathematician's introduction to H( control theory, one of the big research areas of the last 15 years. Worst-case identification (discussed in Chapters 3,4, and 6) is a major area of modern systems theory to which the author has made many contributions. This book gives the first theoretical treatment of this area: it includes much practical material on input design and identification algorithms. Sampling and systems processing is another active area of research. The book presents an accessible treatment of several advanced topics, some included for the first time in any book.

Seller Inventory # LU-9780198500247

Bibliographic Details

• Title: Interpolation, Identification, and Sampling
• Publisher: Oxford University Press, GB
• Publication Date: 1997
• Language: English
• ISBN 10: 0198500246
• ISBN 13: 9780198500247
• Binding: Hardback
• Edition: Illustrated.
• Condition: New
• Dimensions: 16W x 2.03H x 23.62D centimeters 16 centimeters width by 2.03 centimeters height by 23.62 centimeters depth
• Weight: 557 grams

About this title

Synopsis

This book applies functional analysis and complex analysis to problems of interpolation in spaces of analytic functions. It examines problems of recovery--producing approximations to functions from measured values. These values may in turn be corrupted by small errors; the book discusses methods for producing good models using this partial and inaccurate information. The practical applications include systems identification, signal processing, and sampling. The book provides mathematical introductions to many important areas of current research, including H( control theory, sampling and systems processing, and the theory of worst-case identification. This is the first formal treatment of worst-case identification, a field where the author is a leading authority, and the discussion includes much practical material on input design and identification algorithms. This material is appropriate for a graduate-level course on function spaces and the operators acting on them.

About the Author

Jonathan Partington is at University of Leeds.