The research of GA optimization neural network weights blind equalization algorithm based on binary coding

被引：0

作者：

Zhang Liyi ^{[1
,2
]}

Liu Yong ^{[3
]}

Liu Ting ^{[1
]}

Sun Yunshan ^{[1
]}

Li Qiang ^{[2
]}

机构：

[1] Tianjin Univ Commerce, Coll Informat Engn, Tianjin 300134, Peoples R China

[2] Tianjin Univ, Sch Elect Informat Engn, Tianjin 300072, Peoples R China

[3] Taiyuan Univ Technol, Coll Informat Engn, Taiyuan 030024, Shanxi, Peoples R China

来源：

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE INFORMATION COMPUTING AND AUTOMATION, VOLS 1-3 | 2008年

基金：

中国博士后科学基金;

关键词：

blind equalization algorithm; neural network; genetic algorithm; initial weight;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

Two-stage optimization project was proposed by applying genetic algorithm to neural network blind equalization. At first, the initialization weight was optimized using the characteristic of genetic algorithm, which is strong global search capability. And then, optimal weight was gained in virtue of the merit of BP algorithm, which is fast local search speed. Simulation shows that, compared with traditional blind equalization based on BP neural network, the convergence speed of proposed algorithm is quickened, state residual error is decreased and BER is reduced.

引用

页码：91 / +

页数：2