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Proceedings Paper

Super-exponential methods for blind deconvolution
Author(s): Ofir Shalvi; Ehud Weinstein
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Paper Abstract

We present a class of iterative methods for solving the problem of blind deconvolution of an unknown possibly non-minimum phase linear system driven by an unobserved input process. The methods converge monotonically at a very fast super-exponential rate to the desired solution in which the inverse of the unknown system is identified, and the input process is recovered up to a delay and possibly a constant phase shift. The proposed methods are universal in the sense that they do not impose any restrictions on the probability distribution of the input process, provided that it is non-Gaussian.

Paper Details

Date Published: 1 December 1991
PDF: 10 pages
Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); doi: 10.1117/12.49772
Show Author Affiliations
Ofir Shalvi, Tel Aviv Univ. (Israel)
Ehud Weinstein, Tel Aviv Univ. (Israel)


Published in SPIE Proceedings Vol. 1565:
Adaptive Signal Processing
Simon Haykin, Editor(s)

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