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Interpolation, Identification, and Sampling
Contributor(s): Partington, Jonathan R. (Author)

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 ISBN: 0198500246     ISBN-13: 9780198500247
Publisher: Clarendon Press
OUR PRICE: $171.00  

Binding Type: Hardcover
Published: October 1997
Qty:

Annotation: 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.
Additional Information
BISAC Categories:
- Mathematics | Transformations
- Mathematics | Mathematical Analysis
- Mathematics | Functional Analysis
Dewey: 515.73
LCCN: 97013157
Physical Information: 0.69" H x 6.14" W x 9.21" L (1.25 lbs) 280 pages
Features: Bibliography, Illustrated, Index
 
Descriptions, Reviews, Etc.
Publisher Description:
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.
 
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