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Title: Gain estimation for an AC power line data network transmitter using a neural-fuzzy network and an improved genetic algorithm
Authors: Lam, HK
Ling, SH
Leung, FHF 
Tam, PKS
Lee, YS
Issue Date: 2003
Source: 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.
Keywords: Gain measurement
Genetic algorithms
Neural networks
Transmitters
Publisher: IEEE
ISBN: 0-7803-7810-5
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.
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