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Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/1391

Title: Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm
Authors: Lam, H. K.
Ling, S. H.
Leung, Frank H. F.
Tam, Peter K. S.
Lee, Yim-shu
Subjects: Gain measurement
Genetic algorithms
Neural networks
Transmitters
Issue Date: 2003
Publisher: IEEE
Citation: FUZZ-IEEE 2003 : proceedings of the 12th IEEE International Conference on Fuzzy Systems : Sunday 25 May-Wednesday 28 May, 2003, St. Louis, Missouri, USA, p. 167-172.
Abstract: This paper presents the estimation of the transmission gain for an AC power line data network in an intelligent home. The estimated gain ensures the transmission reliability and efficiency. A neural-fuzzy network with rule switches is proposed to perform the estimation. An improved genetic algorithm is proposed to tune the parameters and the rules of the proposed neural-fuzzy network. By turning on or off the rule switches, an optimal rule base can be obtained. An application example will be given.
Rights: © 2003 IEEE. 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.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Type: Conference Paper
URI: http://hdl.handle.net/10397/1391
ISBN: 0-7803-7810-5
Appears in Collections:EIE Conference Papers & Presentations

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