Thursday 25th of April 2024
 

Environmental Noise Classification and Cancellation using Fuzzy Classifier and Fuzzy Adaptive Filters


T. Meera Devi, N. Kasthuri and A. M. Natarajan

The background noise is one of the major factors, which adversely affects the perceived grade of service in audio communication systems. The main problem in most of the environmental noise reduction system is source of noise signal which is to be used as a reference signal. Once the noise source is known then the noise elimination process will become easier. In any environmental conditions, predominant noise signal which is corrupting the original speech signal can be identified using neural network classification. In conventional gradient-based learning algorithms, tuning methods need to be differentiable and it leads to slow in convergence and if the noise is nonlinear, it will not provide a good generalization performance. To overcome this, an automatic noise reduction system is proposed which is an integration of fuzzy classifier and fuzzy adaptive filter.

Keywords: Fuzzy Inference System, Adaptive Filter, Fuzzy Adaptive Wiener filter, MELfrequency coefficients, Independent Component Analysis

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ABOUT THE AUTHORS

T. Meera Devi
Department of Eledtronics and Communication Kongu Engineering College, Perundurai Erode Presented 25 papers in journals, National and International conferences.

N. Kasthuri
Department of Eledtronics and Communication Kongu Engineering College, Perundurai Erode Presented 14 papers in National and Internationa Journals and 50 papers in National and International Conferences

A. M. Natarajan
Department of CSE Bannari Amman Institute of Technolgy Sathyamangalam Published 150 papers in National and International journals.


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