Al-Naffouri, Tareq Yousef (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.
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)|
|Divisions:||College Of Engineering Sciences > Electrical Engineering Dept|
|Creators:||Al-Naffouri, Tareq Yousef|
|Committee Advisor:||Bettayeb, Mammar|
|Committee Members:||Zerguine, Azzedine and Kousa, Maan A. G. and Al-Duwaish, Hussain and Belghonaim, Adil and Fahmy, Moustafa M.|
|Deposited By:||KFUPM ePrints Admin|
|Deposited On:||22 Jun 2008 16:59|
|Last Modified:||25 Apr 2011 10:25|
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