Study of Adaptive Equalizers Based on Two Weighted Neural Networks

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Fourth International Conference on Computer and Information Technology (CIT'04)

Wuhan, China

September 14-September 16

ISBN: 0-7695-2216-5

	ASCII Text	x
	Wenming Cao, Shoujue Wang, "Study of Adaptive Equalizers Based on Two Weighted Neural Networks," Computer and Information Technology, International Conference on, pp. 612-615, Fourth International Conference on Computer and Information Technology (CIT'04), 2004.

	BibTex	x
	@article{ 10.1109/CIT.2004.1357262, author = {Wenming Cao and Shoujue Wang}, title = {Study of Adaptive Equalizers Based on Two Weighted Neural Networks}, journal ={Computer and Information Technology, International Conference on}, volume = {0}, year = {2004}, isbn = {0-7695-2216-5}, pages = {612-615}, doi = {http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357262}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer and Information Technology, International Conference on TI - Study of Adaptive Equalizers Based on Two Weighted Neural Networks SN - 0-7695-2216-5 SP612 EP615 A1 - Wenming Cao, A1 - Shoujue Wang, PY - 2004 KW - Two weighted neural network KW - Channel equalization KW - kernel weigh. VL - 0 JA - Computer and Information Technology, International Conference on ER -

Wenming Cao, Zhejiang University of Technology

Shoujue Wang, Chinese Academy of Science

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CIT.2004.1357262

This paper examines a method to apply to channel equalization problem by model selection. The selection process is based on finding a subset model to approximate the response of the full two weighted neural network model for the current input vector, and not for the entire input space. When the channel equalization problem is non-stationary, the requirement to update all the kernel weighs locations is removed, and its complexity is reduced. Using computer simulations, we show that the number of kernel weighs can be greatly reduced without compromising classification performance.

Index Terms:

Two weighted neural network, Channel equalization, kernel weigh.

Citation:

Wenming Cao, Shoujue Wang, "Study of Adaptive Equalizers Based on Two Weighted Neural Networks," cit, pp.612-615, Fourth International Conference on Computer and Information Technology (CIT'04), 2004

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