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An Experimental Application of the Learnable Evolution Model and Genetic Algorithms to Parameter Estimation in Digital Signal Filters Design

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dc.contributor.author Coletti, Mark
dc.contributor.author Lash, Thomas D.
dc.contributor.author Mandsager, Craig
dc.contributor.author Moustafa, Rida E.
dc.contributor.author Michalski, Ryszard S.
dc.date.accessioned 2006-12-13T19:12:28Z
dc.date.available 2006-12-13T19:12:28Z
dc.date.issued 1999-05 en_US
dc.identifier.citation Coletti, M., Lash, T., Mandsager, C., Moustafa, R. and Michalski, R. S., "An Experimental Application of the Learnable Evolution Model and Genetic Algorithms to Parameter Estimation in Digital Signal Filters Design," Reports of the Machine Learning and Inference Laboratory, MLI 99-5, George Mason University, Fairfax, VA, May 1999. en_US
dc.identifier.uri https://hdl.handle.net/1920/1859
dc.format.extent 1150850 bytes
dc.format.extent 211492 bytes
dc.format.mimetype application/postscript
dc.format.mimetype application/pdf
dc.language.iso en_US en_US
dc.relation.ispartofseries P 99-5 en_US
dc.title An Experimental Application of the Learnable Evolution Model and Genetic Algorithms to Parameter Estimation in Digital Signal Filters Design en_US
dc.type Technical report en_US


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