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Convergence Analysis of a Cascade Architecture Neural Network

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dc.contributor.author Duong, Tuan A. en_US
dc.contributor.author Stubberub, Allen R. en_US
dc.contributor.author Daud, Taher en_US
dc.contributor.author Thakoor, Anil en_US
dc.date.accessioned 2004-09-27T16:11:42Z
dc.date.available 2004-09-27T16:11:42Z
dc.date.issued 1997-08 en_US
dc.identifier.citation USA en_US
dc.identifier.clearanceno 97-1109 en_US
dc.identifier.uri http://hdl.handle.net/2014/22598
dc.description.abstract In this paper, we present a mathematical foundation, including a convergence analysis, for cascading architecture neural networks. From this, a mathematical foundation for the casade correlation learning algorithm can also be found. Furthermore, it becomes apparent that the cascade correlation scheme is a special case of an efficient hardware learning algorithm called Cascade Error Projection. en_US
dc.format.extent 362021 bytes
dc.format.mimetype application/pdf
dc.language.iso en_US
dc.subject.other Neural Network en_US
dc.title Convergence Analysis of a Cascade Architecture Neural Network en_US


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