Advanced Topics in Shannon Sampling and Interpolation Theory

✍ Scribed by Martin J. Bastiaans (auth.), Robert J. Marks II (eds.)

Publisher: Springer-Verlag New York
Year: 1993
Tongue: English
Leaves: 363
Series: Springer Texts in Electrical Engineering
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

Advanced Topics in Shannon Sampling and Interpolation Theoryis the second volume of a textbook on signal analysis solelydevoted to the topic of sampling and restoration of continuous time signals and images. Sampling and reconstruction are fundamental problems in any field that deals with real-time signals or images, including communication engineering, image processing, seismology, speech recognition, and digital signal processing. This second volume includes contributions from leading researchers in the field on such topics as Gabor's signal expansion, sampling in optical image formation, linear prediction theory, polar and spiral sampling theory, interpolation from nonuniform samples, an extension of Papoulis's generalized sampling expansion to higher dimensions, and applications of sampling theory to optics and to time-frequency representations. The exhaustive bibliography on Shannon sampling theory will make this an invaluable research tool as well as an excellent text for students planning further research in the field.

✦ Table of Contents

Front Matter....Pages i-xiii
Gabor’s Signal Expansion and Its Relation to Sampling of the Sliding-Window Spectrum....Pages 1-35
Sampling in Optics....Pages 37-83
A Multidimensional Extension of Papoulis’ Generalized Sampling Expansion with the Application in Minimum Density Sampling....Pages 85-119
Nonuniform Sampling....Pages 121-156
Linear Prediction by Samples from the Past....Pages 157-183
Polar, Spiral, and Generalized Sampling and Interpolation....Pages 185-218
Error Analysis in Application of Generalizations of the Sampling Theorem....Pages 219-298
Back Matter....Pages 299-360

✦ Subjects

Electrical Engineering; Models and Principles; Math. Applications in Chemistry; Computational Intelligence

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