National Changhua University of Education Institutional Repository : Item 987654321/1727

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NCUEIR > College of Engineering > Department and Graduate Institute of Computer Science and Information Engineering > Periodical Articles > Item 987654321/1727

Please use this identifier to cite or link to this item: http://ir.ncue.edu.tw/ir/handle/987654321/1727

Title:	FPGA Realization of a Radial Basis Function Based Nonlinear Channel Equalizer
Authors:	Poyueh Chen;Hungming Tsai;ChengJian Lin;ChiYung Lee
Contributors:	資訊工程學系
Date:	2005
Issue Date:	2010-11-12T07:12:13Z
Abstract:	In this paper we propose a radial basis function (RBF) neural network for nonlinear time-invariant channel equalizer. The RBF network model has a three-layer structure which is comprised of an input layer, a hidden layer and an output layer. The learning algorithm consists of unsupervised learning and supervised learning. The unsupervised learning mainly adjusts the weight among input layer and hidden layer. The supervised learning adjusts the weight among output layer and hidden layer. We will implement RBF by using FPGA. Computer simulation results show that the bit error rates of the RBF equalize using software and hardware implements are close to that of the optimal equalizer.
Relation:	Lecture Notes in Computer Science, 3498(3), 2005:320-325
Appears in Collections:	[Department and Graduate Institute of Computer Science and Information Engineering] Periodical Articles

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