Conference Paper
An improved proportionate NLMS algorithm based on the l0 norm
Telecommun. Dept., Univ. Politeh. of Bucharest, Bucharest, Romania
DOI: 10.1109/ICASSP.2010.5495903 Conference: Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on Source: IEEE Xplore

Conference Paper: A Technical Review on Adaptive Algorithms for Acoustic Echo Cancellation
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ABSTRACT: Acoustic echo is one of the most important issues in communication. It creates disturbance in daytoday communication. This echo can be cancelled using adaptive filters which are governed by adaptive algorithms. Right from the introduction of Least Mean Square (LMS) algorithm, over the years, a lot of research has been done in this field in order to develop new algorithms which can effectively drive the filter to give better performance. In this review paper, we have studied and discussed all the previous work done on these algorithms in relation to acoustic echo cancellation. This paper contains the basic review of all such existing algorithms as well as their merits and demerits. It covers the basic algorithms like LMS algorithm,Recursive Least Square algorithm as well as their modified versions like Normalized Least Mean Square algorithm, Fractional Least Mean Square algorithm, Filteredx Least Mean Square algorithm etc. Finally, a tabular comparison has been given towards the end of the paper in order to conclude the discussion.IEEE Sponsored International Conference on Communication and Signal Processing, India; 04/2014  International Journal of Applied Engineering Research. 10/2014; 9(17):37813805.
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ABSTRACT: Acoustic echo is one of the most important issues in full duplex communication. The original speech signal is distorted due to echo. For this adaptive filtering is used for echo suppression. In this paper our objective is to cancel out the acoustic echo in a sparse transmission channel. For this purpose many algorithms have been developed over the period of time, such as Least Mean Square (LMS), Normalized LMS (NLMS), Proportionate NLMS (PNLMS) and Improved PNLMS (IPNLMS) algorithm. Of all these algorithms we carry out a comparative analysis based on various performance parameters such as Echo Return Loss Enhancement, Mean Square Error and Normalized Projection Misalignment and find that for the sparse transmission channel all these algorithm are inefficient. Hence we propose a new algorithm modified mu  PNLMS, which has the fastest steady state convergence and is the most stable among all the existing algorithms, this we show based on the simulation results obtained.Springer International Conference On Advanced Computing, Networking and Informatics, India; 06/2014
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