Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/489
Title: Artificial neural network approach for parameter estimation of exponentially damped sinusoids using linear prediction
Authors: Swain, A K
Subudhi, B
Keywords: Singular value decomposition
artificial neural networks
linear predictive coding
backward linear prediction
Issue Date: 1997
Publisher: Indian Institute of Science, Bangalore
Citation: Journal of Indian Institute of Science, Vol 77, Iss 1, 63-69
Abstract: The 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.
Description: Copyright belongs to Indian Institute of Science
URI: http://journal.library.iisc.ernet.in/archives/V77-1.html
http://hdl.handle.net/2080/489
Appears in Collections:Journal Articles

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