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基于RBF神经网络的混沌背景下瞬态弱信号检测
引用本文:朱丽莉,张永顺,李兴成.基于RBF神经网络的混沌背景下瞬态弱信号检测[J].空军工程大学学报,2006,7(2):61-63.
作者姓名:朱丽莉  张永顺  李兴成
作者单位:空军工程大学,导弹学院,陕西,三原,713800;空军工程大学,导弹学院,陕西,三原,713800;空军工程大学,导弹学院,陕西,三原,713800
摘    要:针对海杂波背景下瞬态弱信号检测的问题,采用海杂波混沌模型,基于神经网络重构混沌序列相空间,提出了基于RBF神经网络预测混沌时间序列和瞬态弱信号检测方案。理论分析和仿真结果表明这种方法能够有效实现混沌背景噪声中瞬态弱信号的检测。

关 键 词:混沌信号  信号检测  RBF神经网络
文章编号:1009-3516(2006)02-0061-03
收稿时间:2005-06-07
修稿时间:2005年6月7日

Transient Signal in Chaos Detection Based on RBF Neural Network
ZHU Li-li,ZHANG Yong-shun,LI Xing-cheng.Transient Signal in Chaos Detection Based on RBF Neural Network[J].Journal of Air Force Engineering University(Natural Science Edition),2006,7(2):61-63.
Authors:ZHU Li-li  ZHANG Yong-shun  LI Xing-cheng
Institution:The Missile Institute, Air Force Engineering University, Sanyuan, Shaanxi 713800, China
Abstract:The detection of weak signal submerged in chaos is discussed in this paper.In classical statistic detection theory the chaotic noise is regarded as a random signal,which will greatly reduce the performance of signal detection.To improve the performance based on chaotic dynamic mechanism,by using neural network to establish forecast model of chaotic time series and restructure its phase space,and based on the neural network's powerful ability of studying and nonlinear processing and local predictability of chaos,the method of neural network prediction and detection weak signal in chaotic time series is proposed,the results of theoretical analysis and simulation indicate that the method is effective.
Keywords:chaotic signal  signal detection  RBF neural network
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