SCFNN-Based Decision Feedback Equalization Robust to Frequency Offset and Phase Noise

NCUIR > College of Electrical Engineering & Computer Science > Department of Communication Engineering > journal & Dissertation > Item 987654321/51528

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/51528

Title:	SCFNN-Based Decision Feedback Equalization Robust to Frequency Offset and Phase Noise
Authors:	Chang,YJ;Ho,CL
Contributors:	通訊工程學系
Keywords:	NEURAL-NETWORK;ALGORITHM;CHANNELS;FILTER
Date:	2011
Issue Date:	2012-03-27 18:55:20 (UTC+8)
Publisher:	國立中央大學
Abstract:	This paper proposes a self-constructing fuzzy neural network-based decision feedback equalizer (SCFNN DFE). An online learning algorithm containing the structure and parameter learning phases is employed in training the SCFNN DFE. Specifically, the feedforward input vector classification and a gradient-descent method are both used in this online learning algorithm. We show by simulations that the proposed SCFNN DFE offers improvement compared to the traditional DFE methods in the presence of frequency offset and phase noise.
Relation:	CIRCUITS SYSTEMS AND SIGNAL PROCESSING
Appears in Collections:	[Department of Communication Engineering] journal & Dissertation

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