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Proceedings Paper

Signal extrapolation based on wavelet representation
Author(s): Xiang-Gen Xia; C.-C. Jay Kuo; Zhen Zhang
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Paper Abstract

The Papoulis-Gerchberg (PG) algorithm is well known for band-limited signal extrapolation. We consider the generalization of the PG algorithm to signals in the wavelet subspaces in this research. The uniqueness of the extrapolation for continuous-time signals is examined, and sufficient conditions on signals and wavelet bases for the generalized PG (GPG) algorithm to converge are given. We also propose a discrete GPG algorithm for discrete-time signal extrapolation, and investigate its convergence. Numerical examples are given to illustrate the performance of the discrete GPG algorithm.

Paper Details

Date Published: 1 November 1993
PDF: 12 pages
Proc. SPIE 2034, Mathematical Imaging: Wavelet Applications in Signal and Image Processing, (1 November 1993); doi: 10.1117/12.162086
Show Author Affiliations
Xiang-Gen Xia, Univ. of Southern California (United States)
C.-C. Jay Kuo, Univ. of Southern California (United States)
Zhen Zhang, Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 2034:
Mathematical Imaging: Wavelet Applications in Signal and Image Processing
Andrew F. Laine, Editor(s)

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