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Please use this identifier to cite or link to this item: http://hdl.handle.net/2259/263

Title: A neural net based scheme for narrowband signal extraction
Authors: Dash, P.K.*
Nanda, P.K.*
Swain, Anjan Kumar
Khincha, H.P.*
Keywords: Narrowband signal extraction
Neural network
Issue Date: Jun-1994
Publisher: IETE
Abstract: This paper proposes an alternative method for extraction of narrow band signal contaminated with varying white noise power. A three layred feedforward network with one hidden layer is suggested in this paper. The internal parameters are updated by employing the widely used backpropagation algorithm and the statistical Cauchy's algorithm. The network uses the tangent hyperbolic function to provide the desired nonlinearity to the scheme.During learning the net is exposed to signals wirh high SNR ranging from +40 dB to +20 dB. However, after learning quite interesting results are obtained for very low SNR of the input signal even up to 0 dB. The training samples for fundamental, 3rd harmonic and 5th harmonic are chosen to be different with a view to exploit the pattern classification feature of the net. Therefore,after termination of training the proposed scheme accomplishes the filtering action successfully. The phenomenon of network paralysis as encountered in BP algorithm is circumvent...
Description: *External Author Vol.40,Nos.2&3,March-June,1994
URI: http://hdl.handle.net/2259/263
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