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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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2016
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| Subjects: | |
| Online Access: | http://umpir.ump.edu.my/id/eprint/17504/7/ftech-2016-rosha-Adaptive%20Line%20Enhancer%20with%20Selectable1.pdf |
| _version_ | 1796992101489049600 |
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| 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 |
| collection | UMP |
| 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. |
| first_indexed | 2024-03-06T12:15:06Z |
| format | Conference or Workshop Item |
| id | UMPir17504 |
| institution | Universiti Malaysia Pahang |
| language | English |
| last_indexed | 2024-03-06T12:15:06Z |
| publishDate | 2016 |
| publisher | IEEE |
| record_format | dspace |
| spelling | UMPir175042018-05-22T06:44:42Z 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 |
| 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 |
| title | 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_short | Adaptive Line Enhancer with Selectable Algorithms based on Noise Eigenvalue Spread |
| title_sort | adaptive line enhancer with selectable algorithms based on noise eigenvalue spread |
| topic | T Technology (General) TA Engineering (General). Civil engineering (General) TK Electrical engineering. Electronics Nuclear engineering |
| url | http://umpir.ump.edu.my/id/eprint/17504/7/ftech-2016-rosha-Adaptive%20Line%20Enhancer%20with%20Selectable1.pdf |
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