Study on fuzzy neural network classifier blind equalization algorithm

被引：7

作者：

Sun, Yunshan ^{[1
]}

Zhang, Liyi ^{[1
]}

Liu, Ting ^{[1
]}

Li, Yanqin ^{[2
]}

机构：

[1] Tianjin Univ Commerce, Coll Informat & Engn, Tianjin, Peoples R China

[2] Taiyuan Univ Technol, Coll Informat & Engn, Taiyuan, Peoples R China

来源：

2006 IEEE INTERNATIONAL CONFERENCE ON INFORMATION ACQUISITION, VOLS 1 AND 2, CONFERENCE PROCEEDINGS | 2006年

关键词：

blind equalization; fuzzy neural network; channel estimation; classification algorithm;

D O I：

10.1109/ICIA.2006.305792

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

As a key technology in the digital communication system, blind equalization algorithm based on fuzzy neural network classifier is proposed. The algorithm overcomes bad judgment error. Channel estimation algorithm and fuzzy neural network classifier were combined to carry out equalization. The primary signal was attained by de-convolution. Judgment range of fuzzy neural network was adjusted dynamically by competition study algorithm, and then blind equalization judgment was realized. The algorithm reduces judgment error and bit-error ratio. The validity is approved by simulation.

引用

页码：595 / 599

页数：5