Tabu Based Back Propagation Algorithm for Performance Improvement in Communication Channels

Please use this identifier to cite or link to this item: http://hdl.handle.net/2080/843

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DC Field	Value	Language
dc.contributor.author	Satapathy, J K	-
dc.contributor.author	Subhashini, K R	-
dc.date.accessioned	2009-05-19T02:46:03Z	-
dc.date.available	2009-05-19T02:46:03Z	-
dc.date.issued	2008	-
dc.identifier.citation	IEEE Region 10 Conference TENCON, Hyderabad, November 19- 21, 2008	en
dc.identifier.uri	http://dx.doi.org/10.1109/TENCON.2008.4766514	-
dc.identifier.uri	http://hdl.handle.net/2080/843	-
dc.description.abstract	This paper presents a new approach to equalization of communication channels using artificial neural networks (ANNs). A novel method of training the ANNs using Tabu based back propagation (TBBP) algorithm is described. The algorithm uses the Tabu search (TS) to improve the performance of the equalizer as it searches for global minima which is many a time escaped while back propagation (BP) algorithm is applied for this purpose. From the results it can be noted that the proposed algorithm improves the classification capability of the ANNs in differentiating the received data.	en
dc.format.extent	234723 bytes	-
dc.format.mimetype	application/pdf	-
dc.language.iso	en	-
dc.publisher	IEEE	en
dc.subject	adaptive equalisers	en
dc.subject	backpropagation	en
dc.subject	neural nets	en
dc.subject	search problems	en
dc.subject	telecommunication channels	en
dc.title	Tabu Based Back Propagation Algorithm for Performance Improvement in Communication Channels	en
dc.type	Article	en
Appears in Collections:	Conference Papers

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