Adaptive filtering using the least-mean mixed-norms algorithm and its application to echo cancellation.

(1997) Adaptive filtering using the least-mean mixed-norms algorithm and its application to echo cancellation. Masters thesis, King Fahd University of Petroleum and Minerals.

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Arabic Abstract

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English Abstract

Echo is a debiliting problem for full-duplex data transmission over the telephone network and hence must be cancelled. This echo tends to divide into two distinct components which exhibit quite different characteristics. The recently proposed least-mean mixed-norms algorithm utilizes this difference to achieve a higher degree of cancellation as compared to the single-norm algorithm that is usually used. In this thesis, the least-mean mixed-norms algorithm is studied for a general pair of error nonlinerities. In particualar, the convergence of the algorithm is studied and its performance is evaluated for both correlated and independent identically-distributed inputs. The calculus of variations is then used to determine the optimum pair of nonlinearities for each input. These optimum nonlinearities are expressed in terms of the additive-noise probability density function (pdf). Approximating the pdf using the Gram-Charlier expansion provides a practical way for implementing the optimal nonlinearities. All of the above theoretical developments encompass and extend many existing results. Simulation was finally used to demonstrate the advantages of the least-mean mixed-norms algorithm over the single-norm algorithm for half-duplex data transmission.

Item Type: Thesis (Masters)
Subjects: Electrical
Divisions: College Of Engineering Sciences > Electrical Engineering Dept
Committee Advisor: Bettayeb, Mammar
Committee Members: Zerguine, Azzedine and Kousa, Maan A. G. and Al-Duwaish, Hussain and Belghonaim, Adil and Fahmy, Moustafa M.
Depositing User: Mr. Admin Admin
Date Deposited: 22 Jun 2008 16:59
Last Modified: 01 Nov 2019 16:58
URI: http://eprints.kfupm.edu.sa/id/eprint/10224