Statistical signal extraction using stable processes

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Statistical signal extraction using stable processes

Show simple item record Balakrishna, N Hareesh, G 2012-04-11T05:58:30Z 2012-04-11T05:58:30Z 2009
dc.identifier.other Statistics and Probability Letters 79 (2009) 851-856
dc.description.abstract The standard models for statistical signal extraction assume that the signal and noise are generated by linear Gaussian processes. The optimum filter weights for those models are derived using the method of minimum mean square error. In the present work we study the properties of signal extraction models under the assumption that signal/noise are generated by symmetric stable processes. The optimum filter is obtained by the method of minimum dispersion. The performance of the new filter is compared with their Gaussian counterparts by simulation. en_US
dc.description.sponsorship Cochin University of Science and Technology en_US
dc.language.iso en en_US
dc.publisher Elsevier en_US
dc.subject Statistical signal extraction en_US
dc.subject Stable process en_US
dc.subject Probability en_US
dc.title Statistical signal extraction using stable processes en_US
dc.type Working Paper en_US

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