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.authorColetti, Mark
dc.contributor.authorLash, Thomas D.
dc.contributor.authorMandsager, Craig
dc.contributor.authorMoustafa, Rida E.
dc.contributor.authorMichalski, Ryszard S.
dc.date.accessioned2006-12-13T19:12:28Z
dc.date.available2006-12-13T19:12:28Z
dc.date.issued1999-05
dc.format.extent1150850 bytes
dc.format.extent211492 bytes
dc.format.mimetypeapplication/postscript
dc.format.mimetypeapplication/pdf
dc.identifier.citationColetti, 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.
dc.identifier.urihttps://hdl.handle.net/1920/1859
dc.language.isoen_US
dc.relation.ispartofseriesP 99-5
dc.titleAn Experimental Application of the Learnable Evolution Model and Genetic Algorithms to Parameter Estimation in Digital Signal Filters Design
dc.typeTechnical report

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