Two-dimensional memory nonlinearities and their application to blind deconvolution problems

Author

Chen, Yuanjie ; Nikias, Chrysostomos L.

Author_Institution

EEB 400, Signal & Image Processing Inst., Univ. of Southern California, Los Angeles, CA, USA

fYear

1992

fDate

7-9 Oct 1992

Firstpage

210

Lastpage

212

Abstract

Blind deconvolution for a nonminimum phase linear time invariant system is possible only if some nonlinear estimates of the input or the higher-order statistics of the output are employed. When the convolutional noise is colored, the optimum estimates becomes memory nonlinear functions of the observations. Closed form solutions for the two-dimensional memory nonlinear MAP estimates depending on only the current observation and the immediately preceding one are derived for the following a priori probability density functions: (1) uniform, (2) Laplace and (3) exponential

Keywords

estimation theory; noise; signal processing; blind deconvolution; convolutional noise; higher-order statistics; maximum a posteriori estimates; nonminimum phase linear time invariant system; probability density functions; two-dimensional memory nonlinearities; Closed-form solution; Convolution; Deconvolution; Higher order statistics; Image processing; Iterative algorithms; Phase estimation; Probability density function; Signal processing; White noise;

fLanguage

English

Publisher

ieee

Conference_Titel

Statistical Signal and Array Processing, 1992. Conference Proceedings., IEEE Sixth SP Workshop on

Conference_Location

Victoria, BC

Print_ISBN

0-7803-0508-6

Type

conf

DOI

10.1109/SSAP.1992.246812

Filename

246812