Full-Text Search:
Home|Journal Papers|About CNKI|User Service|FAQ|Contact Us|中文
《Computer Engineering and Applications》 2008-07
Add to Favorite Get Latest Update

Application of fuzzy neural network classifier in blind equalization algorithm.

SUN Yun-shan1,LI Yan-qin2,ZHANG Li-yi1,3 1.Department of Information Engineering,Tianjin University of Commerce,Tianjin 300134,China 2.Department of Automation,Institute of Disaster Prevention Science and Technology,Beijing 101601,China 3.Department of Electric Information Engineering,Tianjin University,Tianjin 300003,China  
A blind equalization algorithm based on fuzzy neural network is proposed.Blind channel estimation and fuzzy neural network classifier are utilized to realize blind equalization.Firstly blind channel estimation is used to identify the character of the channel.Signals are rebuilt by de-convolution,and the original judgment equipment is replaced by fuzzy neural network classifier.Simulations indicate that the novel algorithm improves convergence and bit error rate and so on.
【Fund】: 中国博士后基金(the Post-doctor Foundation of China under Grant No.20060390170);; 天津市高等学校科技发展基金(the Tianjin College Science and Technology Development Foundation of China under Grant No.20060610)
【CateGory Index】: TP183;TN911.5
Download(CAJ format) Download(PDF format)
CAJViewer7.0 supports all the CNKI file formats; AdobeReader only supports the PDF format.
©2006 Tsinghua Tongfang Knowledge Network Technology Co., Ltd.(Beijing)(TTKN) All rights reserved