Decorrelation By Principal Component Analysis For Multi Channel Acoustic Echo Cancellation System
Lekshmi T1, Smitha P S2
1Lekshmi T, Department of Electronics and Communication Engineering, Sree Chitra Thirunal College of Engineering, Pappanamcode, Trivandrum (Kerala), India.
2Smitha. P.S, Assistant Professor, Department of Electronics and Communication Engineering, Sree Chitra Thirunal College of Engineering, Pappanamcode, Trivandrum (Kerala), India.
Manuscript received on 13 June 2016 | Revised Manuscript received on 20 June 2016 | Manuscript Published on 30 June 2016 | PP: 113-116 | Volume-5 Issue-5, June 2016 | Retrieval Number: E4620065516/16©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In multi-channel acoustic echo cancellation (MAEC) system, thenon-uniqueness problem and misalignment problem occurs due to the correlation between the reference signals. It could affect convergence performance of the adaptive filtering. So many methods are proposed to get minimum error rate. In this paper, fuzzy logic is used to get minimum error function. The decorrelation is applied through the PCA method. The adaptive fuzzy fusion algorithm improvises, update and check operators obtain optimal solution for defined objective function. To obtain better solution the control parameters are adjusted. It achieves a superior performance in the echo reduction gain and offers the possibility of frequency selective decorrelation to further preserve the sound quality of the system. Simulationresult for the proposed algorithm has shown a significant improvement in convergence rate compared with existing system.
Keywords: Multi Channel AEC, Non-Uniqueness Problem, Misalignment Problem, Principal Component Analysis.
Scope of the Article: Problem Solving and Planning