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Artificial Neural Net Based Noise Cancellor

Dash, PK and Saha, S and Nanda, PK and Khincha, HP (1991) Artificial Neural Net Based Noise Cancellor. In: Proceedings of ACE’90 (XVI Annual Convention and Exhibition of the IEEE in India), 22-25 January 1991, Bangalore, India, pp. 37-41.

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Abstract

This paper presents a new method for noise cancellation with an Artificial Neural Network. The network used is a feedforward one with three layers . The Back propagation and stastical Cauchy’s learning a1gorithms are employed for adaptation of the internal parameters of the network. The constrained tangent hyperbolic function is used to activate the neurons and to provide the desired non-1inearity. Promising simulation results for noise cancellation intensify the validity of superseding the proposed scheme for many existing techniques. To demonstrate the effectiveness, the proposed method is applied to different input conditions with varying SMRs. With incomplete signal samples the net is found to produce output having a striking resemblance with that of the desired ones. A performance comparison of the two algorithms is presented in the paper for better appraisal.

Item Type: Conference Paper
Additional Information: ©1991 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 28 Jun 2004
Last Modified: 19 Sep 2010 04:12
URI: http://eprints.iisc.ernet.in/id/eprint/440

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