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Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/489

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contributor.authorSwain, A K-
contributor.authorSubudhi, B-
date.accessioned2007-09-18T07:06:20Z-
date.available2007-09-18T07:06:20Z-
date.issued1997-
identifier.citationJournal of Indian Institute of Science, Vol 77, Iss 1, 63-69en
identifier.urihttp://journal.library.iisc.ernet.in/archives/V77-1.html-
identifier.urihttp://hdl.handle.net/2080/489-
descriptionCopyright belongs to Indian Institute of Scienceen
description.abstractThe paper presents a neural net-based scheme embodying linear prediction techniques and the SVD algorithm to estiimate the parameters of exponetially damped sinusoids satisfactorly under low SNR conditions. In the method proposed a three layer feed-forward neural network is employed at the output of the SVD block for suppressing bias in the estimated singular values due to the presence of noise. The ANN block is used to keep the singular values constant at their noiseless counterpart, even at SNR less than 0 dB. The method is considered to be the most efficient for parameter estimation at very low SNR.en
format.extent1586264 bytes-
format.mimetypeapplication/pdf-
language.isoen-
publisherIndian Institute of Science, Bangaloreen
subjectSingular value decompositionen
subjectartificial neural networksen
subjectlinear predictive codingen
subjectbackward linear predictionen
titleArtificial neural network approach for parameter estimation of exponentially damped sinusoids using linear predictionen
typeArticleen
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