Fast self-constructing fuzzy neural network-based decision feedback equaliser in time-invariant and time-varying channels

NCUIR > College of Electrical Engineering & Computer Science > Department of Communication Engineering > journal & Dissertation > Item 987654321/51485

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51485

Title:	Fast self-constructing fuzzy neural network-based decision feedback equaliser in time-invariant and time-varying channels
Authors:	Chang,YJ;Yang,SS;Ho,CL
Contributors:	通訊工程學系
Keywords:	ALGORITHM
Date:	2010
Issue Date:	2012-03-27 18:54:09 (UTC+8)
Publisher:	國立中央大學
Abstract:	A fast self-constructing fuzzy neural network-based decision feedback equaliser (FSCFNN DFE) is proposed. Without estimating the channel, a fast learning algorithm containing the structure and parameter learning phases is employed to the FSCFNN DFE. Both the partition of the feedforward input space and the gradient descent method are used simultaneously with the aid of decision feedback inputs in this fast learning procedure. The performance of FSCFNN DFE is compared with traditional non-linear equalisers in both time-invariant and time-varying channels. The reduced complexity and excellent performance of the FSCFNN DFE make it suitable for severely distorted channel equalisation.
Relation:	IET COMMUNICATIONS
Appears in Collections:	[Department of Communication Engineering] journal & Dissertation

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