Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread

Adaptive efficient mechanism eliminates varying environmental noise embedded in speech signals, since the eigenvalue spread has a great influence on the convergence behavior of adaptive algorithms. The inefficient least mean square (LMS) algorithm for ill-conditioned signals, with high eigenvalue sp...

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Main Authors:	Roshahliza, M. Ramli, Noor, Ali O. Abid, Salina, Abdul Samad
Format:	Conference or Workshop Item
Language:	English
Published:	IEEE 2016
Subjects:	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/17504/ http://umpir.ump.edu.my/id/eprint/17504/ http://umpir.ump.edu.my/id/eprint/17504/7/ftech-2016-rosha-Adaptive%20Line%20Enhancer%20with%20Selectable1.pdf

id	ump-17504
recordtype	eprints
spelling	ump-175042018-05-22T06:44:42Z http://umpir.ump.edu.my/id/eprint/17504/ Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Adaptive efficient mechanism eliminates varying environmental noise embedded in speech signals, since the eigenvalue spread has a great influence on the convergence behavior of adaptive algorithms. The inefficient least mean square (LMS) algorithm for ill-conditioned signals, with high eigenvalue spread in the autocorrelation matrix, hence slow convergence and degraded signal quality are observed. Meanwhile, the Recursive Least Squares (RLS) solved this problem at the expense of high computational power. For these purposes, adaptive filtering offers a viable alternative to be used in various noise cancellation applications. In this paper, adaptive set-membership filtering based on a combination of a selective adaptive line enhancer with optimized set-membership filtering approach for single input noise cancellation system was proposed. The adaptive selection from a set of multiple adaptive algorithms to operate according to the characteristics of noise signals. The simulation results showed the capability of proposed algorithm to eliminate different types of environmental noise with fast convergence, reduction in computational complexity and improvement in signal-to-noise ratio when compared with an equivalent system using a single adaptive algorithm. The computational complexity of the proposed approach showed reduction of nearly 90% compared to the RLS and converged in about 6.25 msec. IEEE 2016 Conference or Workshop Item PeerReviewed application/pdf en http://umpir.ump.edu.my/id/eprint/17504/7/ftech-2016-rosha-Adaptive%20Line%20Enhancer%20with%20Selectable1.pdf Roshahliza, M. Ramli and Noor, Ali O. Abid and Salina, Abdul Samad (2016) Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread. In: IEEE International Conference on Advances in Electrical, Electronic and System Engineering (ICAEESE 2016), 14-16 November 2016 , Putrajaya, Malaysia. pp. 374-379.. ISBN 978-1-5090-2888-7 https://doi.org/10.1109/ICAEES.2016.7888069
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering
spellingShingle	T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread
description	Adaptive efficient mechanism eliminates varying environmental noise embedded in speech signals, since the eigenvalue spread has a great influence on the convergence behavior of adaptive algorithms. The inefficient least mean square (LMS) algorithm for ill-conditioned signals, with high eigenvalue spread in the autocorrelation matrix, hence slow convergence and degraded signal quality are observed. Meanwhile, the Recursive Least Squares (RLS) solved this problem at the expense of high computational power. For these purposes, adaptive filtering offers a viable alternative to be used in various noise cancellation applications. In this paper, adaptive set-membership filtering based on a combination of a selective adaptive line enhancer with optimized set-membership filtering approach for single input noise cancellation system was proposed. The adaptive selection from a set of multiple adaptive algorithms to operate according to the characteristics of noise signals. The simulation results showed the capability of proposed algorithm to eliminate different types of environmental noise with fast convergence, reduction in computational complexity and improvement in signal-to-noise ratio when compared with an equivalent system using a single adaptive algorithm. The computational complexity of the proposed approach showed reduction of nearly 90% compared to the RLS and converged in about 6.25 msec.
format	Conference or Workshop Item
author	Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad
author_facet	Roshahliza, M. Ramli Noor, Ali O. Abid Salina, Abdul Samad
author_sort	Roshahliza, M. Ramli
title	Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread
title_short	Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread
title_full	Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread
title_fullStr	Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread
title_full_unstemmed	Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread
title_sort	adaptive line enhancer with selectable algorithms based on noise eigenvalue spread
publisher	IEEE
publishDate	2016
url	http://umpir.ump.edu.my/id/eprint/17504/ http://umpir.ump.edu.my/id/eprint/17504/ http://umpir.ump.edu.my/id/eprint/17504/7/ftech-2016-rosha-Adaptive%20Line%20Enhancer%20with%20Selectable1.pdf
first_indexed	2023-09-18T22:24:13Z
last_indexed	2023-09-18T22:24:13Z
_version_	1777415857726554112

Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread

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