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Artificial neural network approach for parameter estimation of exponentially damped sinusoids using linear prediction

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dc.contributor.author Swain, Anjan Kumar
dc.contributor.author Subudhi, B.*
dc.date.accessioned 2015-03-19T09:23:21Z
dc.date.available 2015-03-19T09:23:21Z
dc.date.issued 1997-02
dc.identifier.uri http://hdl.handle.net/2259/251
dc.description * External Author en_US
dc.description.abstract he 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_US
dc.language.iso en en_US
dc.publisher Indian Institute of Science en_US
dc.subject Singular value decomposition en_US
dc.subject artificial neural networks en_US
dc.subject linear predictive coding en_US
dc.subject backward linear prediction en_US
dc.title Artificial neural network approach for parameter estimation of exponentially damped sinusoids using linear prediction en_US
dc.type Article en_US


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