摘要
为了有效地盲估计出混沌直扩序列,利用神经网络能无限任意逼近非线性函数的特点,设计了一种改进型的基于神经网络盲估计混沌扩频序列的方法,该方法增加了信号盲分离模块。仿真结果表明,该方法无须搜索信息码与扩频序列之间的同步点,即使是在较低信噪比的条件下,仍能有效地从噪声背景中盲分离出混沌扩频信号,并盲估计出原始混沌序列。
In order to blind estimate chaoti direct spread spectrum effectively,based on the neural network,this paper proposed an improved method to blind estimate the chaotic spread spectrum sequences.This method took full advantages of the neural network＇s nonlinearity and increased the blind signal separation module.The simulation results show that it does not need to search a synchronous point between symbol waveform and chaotic sequences.By using the method,the chaotic spread spectrum signals can be effectively blind separated from noisy background,and the original chaotic sequences can be exactly blind estimated even when the signal to noise ration is low.
出处
《计算机应用研究》
CSCD
北大核心
2011年第4期1518-1520,共3页
Application Research of Computers
基金
重庆市科委自然科学基金计划资助项目(2007ba2017)
关键词
混沌扩频序列
盲分离
神经网络
盲估计
chaotic spread spectrum sequences
blind separation
neural network
blind estimation
