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Analysis and generalization of a median adaptive filter

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2 Author(s)
Haweel, T.I. ; Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA ; Clarkson, P.M.

A class of gradient based adaptive algorithms is presented which employs order-statistical transformations of the gradient estimates over a short window. These algorithms, called order-statistical least mean squares (OSLMS), are designed to facilitate adaptive filter performance close to the least-squares optimum in impulsive and other non-Gaussian input environments. Three specific OSLMS filters are defined: the median LMS, the averaged LMS, and the trimmed-mean LMS. For the median LMS some simple convergence results are given. Simulations of all three algorithms, conducted using a generalized exponential density, are presented

Published in:

Acoustics, Speech, and Signal Processing, 1990. ICASSP-90., 1990 International Conference on

Date of Conference:

3-6 Apr 1990