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Performance Analysis of an Affine Combination of Two LMS Adaptive Filters

Published on March 2012 by Abdullah M.K., F.I.Shaikh, A.I.Tamboli
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International Conference in Computational Intelligence
Foundation of Computer Science USA
ICCIA - Number 5
March 2012
Authors: Abdullah M.K., F.I.Shaikh, A.I.Tamboli
d7052bc4-e423-49e2-9993-3cd19a54bfd6

Abdullah M.K., F.I.Shaikh, A.I.Tamboli . Performance Analysis of an Affine Combination of Two LMS Adaptive Filters. International Conference in Computational Intelligence. ICCIA, 5 (March 2012), 16-20.

@article{
author = { Abdullah M.K., F.I.Shaikh, A.I.Tamboli },
title = { Performance Analysis of an Affine Combination of Two LMS Adaptive Filters },
journal = { International Conference in Computational Intelligence },
issue_date = { March 2012 },
volume = { ICCIA },
number = { 5 },
month = { March },
year = { 2012 },
issn = 0975-8887,
pages = { 16-20 },
numpages = 5,
url = { /proceedings/iccia/number5/5123-1035/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 International Conference in Computational Intelligence
%A Abdullah M.K.
%A F.I.Shaikh
%A A.I.Tamboli
%T Performance Analysis of an Affine Combination of Two LMS Adaptive Filters
%J International Conference in Computational Intelligence
%@ 0975-8887
%V ICCIA
%N 5
%P 16-20
%D 2012
%I International Journal of Computer Applications
Abstract

This paper studies the statistical behavior of an affine combination of the outputs of two least mean-square (LMS) adaptive filters that simultaneously adapt using the same white Gaussian inputs. The purpose to combine two filters is to obtain a new LMS adaptive filter with fast convergence and small steady-state mean-square deviation (MSD).The linear combination studied is generalization of convex combination in which combination factor ?(n) is restricted to the interval (0,1).Each of the two filters produces dependent estimates of unknown channel. Thus there exists a sequence of optimal affine combining coefficients which minimizes the mean-square error (MSE) and gives good steady state response. First optimal unrealizable affine combiner is studied. Then two schemes proposed to find out the optimal mixing parameter to get optimized sequence ?(n) are stochastic gradient approach and error power based scheme. The mean square performances are analyzed and validated by MATLAB7.

References
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  2. S. Haykin, Adaptive Filter Theory, 2nd ed. Englewood Cliffs, NJ: Prentice-Hall, 1991.
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  4. N.J.Bershard and A.Bist,”Fast coupled adaptation for sparse impulse responses using partial Haar transform,” IEEETrans. Signal Process., vol.53,no.3,pp966-976,Mar 2005.
  5. D. G. Manolakis, V. K. Inglr, and S. M.Kogon, Statistical and Adaptive Signal Processing. Boston, MA: McGraw-Hill, 1999.
  6. R. Candido, M. T. M. Silva, and V. Nascimento, “Affine combinations of adaptive filters,” in Proc. of the Asilomar Conference on Signals, Systems, and Computers, Pacific Grove, CA, U.S.A., Oct. 2008, IEEE.
  7. A. T. Erdogan, S. S. Kozat, and A. C. Singer, “Comparison of convex combination and affine combination of adaptive filters,” in Proc. of the IEEE International Conference on Acoustics, Speech and Signal Processing, Taiwan, Apr. 2009, pp. 3089–3092.
Index Terms

Computer Science
Information Sciences

Keywords

Adaptive filters affine combination convex combination least mean square (LMS)