摘要
利用动力系统方法研究了几种跳频码 (m序列 ,RS序列 ,非线性序列及混沌序列 )的动力学特性 (相关维数与最大李雅普诺夫指数 ) ,结果表明了跳频码表现出混沌的特征。最后根据遗传算法确定前馈神经网络的结构 ,并利用该神经网络模型对这几种序列做了预测分析。实验结果表明 ,该模型能成功地预测跳频码 。
In this paper,the dynamic characteristics(correlation dimension and the largest Lyapunov exponents)of some kinds of FH codes( m sequences, RS sequences,nonlinear sequences and chaotic sequences)by dynamic system method are studied.The results show that FH codes are of chaotic characteristics.Finally,on basis of genetic algorithms,the neural networks structure is determined,furthermore,and predictive analysis of these kind of FH codes is made by using neural networks model .Experimental results show that this model can predict FH codes,therefore it is able to interfere FH communications.\;
出处
《系统工程与电子技术》
EI
CSCD
2000年第12期29-32,100,共5页
Systems Engineering and Electronics
基金
国防预研基金资助课题! (98JS0 5 4 1 D Z0 2 0 5 )
关键词
跳频通信
跳频码
混纯动力学
预测
Frequency hopping communication Dynamics Lyapunov function
