A Noise Cleaning Method for Chaotic Time Series and Its Application in Communication

A new algorithm for filtering highly noisy contaminated chaotic time series is proposed and realized. It is indicated by computer simulation that this algorithm can effectively reduce noise on chaotic signal no mater how parameter of chaos generator varies with time. In comparison with the extended-Kalman-filter-based method, this algorithm has a better filtering performance in the case of low signal-to-noise (SNR) ratios, and has the similar performance in the case of high SNR. In addition, a chaotic modulation communication system is also used to evaluate the performance of the algorithm, the result shows the effectiveness of the method.     

Identification of Chaotic Systems with Application to Chaotic Communication

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.     

Filtering noisy chaotic signal via sparse representation based on random frame dictionary

The denoising problem of impure chaotic signals is addressed in this paper. A method based on sparse representation is proposed, in which the random frame dictionary is generated by a chaotic random search algorithm. The numerical simulation shows the proposed algorithm outperforms those recently reported alternative denoising methods.     

基于Huber的高阶容积卡尔曼跟踪算法

为改善高阶容积卡尔曼滤波算法的滤波精度和鲁棒性, 提出了一种新的基于Huber的高阶容积卡尔曼滤波算法. 在采用统计线性回归模型近似非线性量测模型的基础上, 利用Huber M 估计算法实现状态的量测更新. 进一步结合高阶球面-径向容积准则的状态预测模块构成基于 Huber的高阶容积卡尔曼跟踪算法. 重点分析了Huber代价函数的调节因子对算法跟踪性能的影响. 通过对纯方位目标跟踪和再入飞行器跟踪两个实例验证了所提算法的跟踪性能优于传统高阶容积卡尔曼滤波算法.     

Gradient method for blind chaotic signal separation based on proliferation exponent

A new method to perform blind separation of chaotic signals is articulated in this paper, which takes advantage of the underlying features in the phase space for identifying various chaotic sources. Without incorporating any prior information about the source equations, the proposed algorithm can not only separate the mixed signals in just a few iterations, but also outperforms the fast independent component analysis(FastICA) method when noise contamination is considerable.     

Blind Extraction of Chaotic Signals by Using the Fast Independent Component Analysis Algorithm

We report the results of using the fast independent component analysis （FastICA） algorithm to realize Mind extraction of chaotic signals. Two cases are taken into consideration： namely, the mixture is noiseless or contaminated by noise. Pre-whitening is employed to reduce the effect of noise before using the FastICA algorithm. The correlation coefficient criterion is adopted to evaluate the performance, and the success rate is defined as a new criterion to indicate the performance with respect to noise or different mixing matrices. Simulation results show that the FastICA algorithm can extract the chaotic signals effectively. The impact of noise, the length of a signal frame, the number of sources and the number of observed mixtures on the performance is investigated in detail It is also shown that regarding a noise as an independent source is not always correct.     

参数失配的受迫振动系统有误差界的同步判据

基于李雅普诺夫直接法和Sylvester准则,推导出外激励参数失配的受迫振动系统达到有误差界的同步的几种代数判据. 根据代数不等式,求得同步误差界的估计值. 通过控制同步误差界估计值,可以把实际的同步误差界值控制到小于预先给定的同步精确度. Duffing-Van der Pol受迫振动系统作为数值算例进一步验证了该方法是有效的. 关键词： 受迫振动系统 参数失配 同步误差界 代数判据     

Dispersion compensation in an open-loop all-optical chaotic communication system

The optical chaotic communication system using open-loop fiber transmission is studied under strong injection conditions. The optical chaotic communication system with open-loop configuration is studied using fiber transmission under strong injection conditions. The performances of fiber links composed of two types of fiber segments in different dispersion compensation maps are compared by testing the quality of the recovered message with different bit rates and encrypted by chaotic modulation (CM) or chaotic shift keying (CSK). The result indicates that the performance of the pre-compensation map is always worst. Two types of symmetrical maps are identical whatever the encryption method and bit-rate of message are. For the transmitting and the recovering of message of lower bit rate (1 Gb/s), the post-compensation map is the best scheme. However, for the message of higher bit rate (2.5 Gb/s), the parameters in communication system need to be modified properly in order to adapt to the high-speed application. Meanwhile, two types of symmetrical maps are the best scheme. In addition, the CM method is superior to the CSK method for high-speed applications. It is in accordance with the result in a back-to-back configuration system.     

开环全光混沌通信系统中的光纤信道结构

根据外光反馈半导体激光器及光纤传输方程,构建了基于光纤信道的开环全光混沌通信系统.考虑混沌调制和混沌键控两种信息加密方法,采用先进的校正相减解调法恢复信息,并且通过解调Q因子衡量系统性能.以不同次序排列单模光纤和色散补偿光纤构成4种结构的光纤信道,通过数值仿真分析信道结构对系统通信性能的影响.结果表明,为光纤信道保留少量的负累积色散有利于改善远程传输性能;两端补偿和中间补偿这两种对称结构的性能一致,对称结构优于非对称结构即预补偿和后补偿,适用于远程高速开环全光混沌通信.另外,无论光纤信道结构怎样,在远程高速激光混沌通信中混沌调制方法总是优于混沌键控方法.