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- W117144483 abstract "Signal Processing Group, Universitat de Vic, Sagrada Fam´ilia 7, 08500, Vic, Spainmbzadeh@yahoo.com, jordi.sole@uvic.es, Christian.Jutten@inpg.frABSTRACTA Wiener system is a linear time-invariant filter,followed by an invertible nonlinear distortion. As-suming that the input signal is an independent andidentically distributed (iid) sequence, we proposean algorithm for estimating the input signal onlyby observing the output of the Wiener system. Thealgorithm is based on minimizing the mutual infor-mation of the output samples, by means of a steep-est descent gradient approach.1. INTRODUCTIONWhen linear models fail, nonlinear models are power-ful tools for modeling practical situations. Many re-searches have been done in the identification and/orthe inversion of nonlinear systems. These works usu-ally assume that both the input and the output of thedistortion are available, and are based on higher-orderinput/outputcross-correlation [1] or on the applicationof the Bussgang and Prices theorems [2, 3] for nonlin-ear systems with Gaussian inputs. However, in a realworld situation, one often does not have access to thedistortion input. In this case, the blind identificationof the nonlinearity becomes the only way to solve theproblem. This paper is concerned by a particular classof nonlinear systems, composed by a linear subsystemfollowed by a memoryless nonlinear distortion (seeFig. 1). This class of nonlinearsystems, also known asWiener systems, is a nice and mathematically attract-ing model, but also an actual model used in variousareas, such as biology [4], industry [5], sociology andpsychology (see also [6] and the references therein).Despite its interest, at our knowledge, it only exist two" @default.
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- W117144483 date "2003-01-01" @default.
- W117144483 modified "2023-09-26" @default.
- W117144483 title "A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions" @default.
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