| Identification of Chaotic Systems with Application to Chaotic Communication |
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| 作者姓名： | 冯久超 邱玉辉 |
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| 作者单位： | [1]FacultyofElectronicandInformationEngineering,SouthwestChinaNormalUniversity,Chongqing400715 [2]DepartmentofComputerScience,SouthwestChinaNormalUniversity,Chongqing400715 |
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| 摘 要： | We propose and develop a novel method to identify a chaotic system with time-varying bifurcation parameters via an observation signal which has been contaminated by additive white Gaussian noise.This method is based on an adaptive algorithm,which takes advantage of the good approximation capability of the radial basis function neural network and the ability of the extended Kalman filter for tracking a time-varying dynamical system.It is demonstrated that,provided the bifurcation parameter varies slowly in a time window,a chaotic dynamical system can be tracked and identified continuously,and the time-varying bifurcation parameter can also be retrieved in a sub-window of time via a simple least-square-fit method.
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| 关 键 词： | 混沌系统 分歧参数 高斯白噪声 神经网络函数 非线性滤波器 |
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