Blind Detection of BPSK Signals Using Hysteretic Hopfield Neural Network

被引：2

作者：

Yu, Shu-Juan ^{[1
]}

Feng, Di ^{[1
]}

Zhang, Yun ^{[1
]}

机构：

[1] Nanjing Univ Posts & Telecommun, Sch Elect Sci & Engn, 66 XingMoFan Rd, Nanjing, Jiangsu, Peoples R China

来源：

PROCEEDINGS OF 2013 CHINESE INTELLIGENT AUTOMATION CONFERENCE: INTELLIGENT AUTOMATION | 2013年 / 254卷

关键词：

Hysteretic Hopfield neural network (HHNN); Blind detetion; BPSK signals;

D O I：

10.1007/978-3-642-38524-7_76

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

A new algorithm based on Hysteretic Hopfield neural nework (HHNN) is proposed to detect BPSK signals blindly. Considering the characteristic of hysteretic activation function, the new algorithm has a tendency to overcome local minima. The new energy functions for HHNN are constructed, and the stability of the network is also analyzed. Simulation results show that the algorithm proposed show satisfactory performance in detecting BPSK with shorter received signals.

引用

页码：693 / 701

页数：9

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