A Highly Efficient Adaptive Channel Equaliser Using Single Layer Architecture

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/22

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DC Field	Value	Language
dc.contributor.author	Panda, G	-
dc.contributor.author	Satpathy, J K	-
dc.contributor.author	Patra, S K	-
dc.date.accessioned	2005-04-23T05:00:40Z	-
dc.date.available	2005-04-23T05:00:40Z	-
dc.date.issued	1992-03	-
dc.identifier.citation	IEEE International Workshop on Intelligent Signal Processing and Communication Systems March 19-21, 1992. P 299 -312	en
dc.identifier.uri	http://hdl.handle.net/2080/22	-
dc.description	Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.	en
dc.description.abstract	This paper propses a highly elegant adaptive equaliser structure using single neuron which possesses significantly low computational complexity compared to recently reported multilayerd Artificial Neural Network Based equaliser. In terms of performance the proposed structure offers minimum residual mean square error in comparision to either the LMS or multilayered based structure. The learning rate of the proposed equalised is faster than that of the multilayered case.	en
dc.format.extent	454897 bytes	-
dc.format.mimetype	application/pdf	-
dc.language.iso	en	-
dc.publisher	IEEE	en
dc.subject	Digital Adaptive Equaliser	en
dc.subject	Artificial Neural Network	en
dc.title	A Highly Efficient Adaptive Channel Equaliser Using Single Layer Architecture	en
dc.type	Article	en
Appears in Collections:	Conference Papers

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