基于状态观测器的超混沌同步保密通信系统

提出了一种基于状态观测器的超混沌同步保密通信系统。用超混沌系统的多个状态量对信息信号进行复杂的加密后注入超混沌系统实现混沌调制,同时将加密后的信息信号混沌掩盖后传送出去。用状态观测器思想实现了发送系统和接收系统的同步,并在接收端将信息信号解密。由于用了超混沌系统的多个状态量对信息信号加密,增加了传输信号的复杂性,提高了通信系统的保密性。     

基于RBF网络的混沌时间序列的建模与多步预测

提出将RBF神经网络应用于混沌时间序列的建模与预测中 ,设计了一个三层RBF网络结构 ,说明了RBF网络用于混沌时间序列建模和预测时的基本性质。仿真结果表明 ,RBF网络模型对混沌时间序列有比较强的拟合能力和比较高的一步及多步预测精度。采用RBF网络进行混沌时间序列的建模和预测能够取得比其它方法好得多的效果。     

Enhanced NTRU cryptosystem eliminating decryption failures

1. INTRODUCTION In 1996, Hoffstein, Pipher and Silverman presented a public key cryptosystem based on polynomial algebra called NTRU [1]. The security of NTRU is based on the hardness of some lattice problems, namely the shortest and the closest vector problems. It is one of the fastest public key encryption schemes known. Because the encryption and decryption process of this system involves polynomials with small coefficients, it is quite fast compared to systems like RSA, El Gamal…     

Construction of Periodic Orbits and Chaos

1 .ＩＮＴＲＯＤＵＣＴＩＯＮＳｉｎｃｅｔｈｅｔｅｒｍ“ｃｈａｏｓ”ｗａｓｆｉｒｓｔｉｎｔｒｏｄｕｃｅｄｉｎＬｉａｎｄＹｏｒｋｅ’ｓｐａｐｅｒ [1 ]ｔｏｄｅｓｃｒｉｂｅｔｈｅｄｙｎａｍｉｃｓｏｆｄｉｓｃｒｅｔｅｓｙｓｔｅｍｓ,ｃｈａｏｓｈａｓｂｅｅｎｅｘｔｅｎｓｉｖｅｌｙｓｔｕｄｉｅｄａｎｄｔｈｅｐｈｅｎｏｍｅｎｏｎｏｆｃｈａｏｓｈａｓｂｅｅｎｏｂｓｅｒｖｅｄｉｎｄｙｎａｍｉｃａｌｓｙｓ ｔｅｍｓｉｎｍａｎｙｄｉｆｆｅｒｅｎｔｆｉｅｌｄｓ.Ａｗｉｄｅｌｙａｃｃｅｐｔｅｄｍａｔｈｅｍａｔｉｃａｌｄｅｆｉ…     

高频雷达海洋回波混沌特性研究

为分析大面积海域海洋回波的混沌特性,使用时间序列相空间重构、时间延迟、嵌入维数、关联维数和Lyapunov指数等混沌特性研究方法。利用海洋状态测量与分析雷达(OSMAR 2000型)获取的时间序列数据,基于Donald E.Barrick提出的线性调频中断连续波(FMICW)雷达信号处理方法和一、二阶海洋表面回波理论,对位于浙江舟山东海岸张角约65°,距离约200 km的扇形海面高海态和低海态回波数据进行了分析处理,证明此类海洋回波具有混沌特征。     

Local prediction of the chaotic fh-code based on LS-SVM

Support vector machine （SVM） is powerful to solve some problems such as nonlinear classification, function estimation and density estimation. To consider the chaotic fh （frequency hopping）-code＇s characters in chaotic dynamic system, the forecasting model of the support vector machine in combination with Takens＇ delay coordinate phase reconstruction of chaotic times is established and the least squares model for large-scale problems is used in local training for this model. Finally, a fh-code series generated by Logistic-Kent mapping is applied to verify the local prediction model. Simulation results show that the high accuracy and fault tolerant SVM model has an excellent performance in predicting the fh code, with a very low mean square error and a high relative coefficient.     

混沌神经网络编码研究

本文运用神经网络的非线性动力学理论，研究了利用线性分段的一波三折函数构造混沌神经网络，进行混沌序列编码。文中分别给出自环反馈网络模型和耦合网络模型，并针对每类模型，仿真得到了具体的网络，获得了相应的混沌编码。同时对耦合网络的模式识别进行了初步探讨。     

基于小波与混沌集成的中国股票市场预测

应用小波变换和混沌理论提出了一种中国股票市场建模及其预测的小波与混沌集成的方法．首先应用小波分解理论对上证综指和深证成指日收益率序列进行分解，分别得到低频部分和高频部分，并在此基础上作进一步分析，结果表明中国股市存在混沌特性；然后应用混沌理论分别建立低频部分和高频部分的预测模型，对低频部分和高频部分进行预测；最后应用小波理论对混沌模型预测的结果予以重构，实现对原始收益率序列的预测．与现有方法比较，结果表明该方法具有较高的精度，有极大的应用前景．     

时滞混沌系统的脉冲同步

针对时滞混沌系统的同步问题,利用脉冲控制方法,提出了新的渐进同步的充分条件。利用脉冲状态反馈控制,在系统矩阵为Hurwitz矩阵和正定矩阵两种情况下,得到了时滞混沌系统同步的充分条件;进一步,为便于工程应用,利用脉冲输出反馈,在系统矩阵为上述两种情况下,得到了时滞混沌系统同步的充分条件。该同步条件使时滞混沌同步系统快速地达到10-2误差。最后,以一个多重时滞混沌系统为例,进行了数值仿真,验证了该方法的有效性。     

随机干扰下降阶时延混沌系统的自适应广义投影同步

研究随机干扰下降阶时延混沌系统的广义投影同步(RLGPSS).结合自适应控制方法和反馈控制技术,设计控制器和参数自适应更新律,实现混沌系统的RLGPSS问题,同时,对于系统未知参数能够有效的辨识.数值仿真结果证实了所提出控制策略的有效性.     

Optimization of HMM Parameters Based on Chaos and Genetic Algorithm for Hand Gesture Recognition

In order to prevent standard genetic algorithm (SGA) from being premature, chaos is introduced into GA, thus forming chaotic anneal genetic algorithm (CAGA). Chaos' ergodicity is used to initialize the population, and chaotic anneal mutation operator is used as the substitute for the mutation operator in SGA. CAGA is a unified framework of the existing chaotic mutation methods. To validate the proposed algorithm, three algorithms, i. e. Baum-Welch, SGA and CAGA, are compared on training hidden Markov model (HMM) to recognize the hand gestures. Experiments on twenty-six alphabetical gestures show the CAGA's validity.     

Periodic performance of the chaotic spread spectrum sequence on finite precision

It is well known that the periodic performance of spread spectrum sequence heavily affects the correlative and secure characteristics of communication systems.The chaotic binary sequence is paid more and more attention since it is one kind of applicable spread spectrum sequences.However,there are unavoidable short cyclic problems for chaotic binary sequences in finite precision.The chaotic binary sequence generating methods are studied first.Then the short cyclic behavior of the chaotic sequences is analyzed in detail,which are generated by quantification approaches with finite word-length.At the same time,a chaotic similar function is defined for presenting the cyclic characteristics of the sequences.Based on these efforts,an improved method with scrambling control for generating chaotic binary sequences is proposed.To quantitatively describe the improvement of periodic performance of the sequences,an orthogonal estimator is also defined.Some simulating results are provided.From the theoretical deduction and the experimental results,it is concluded that the proposed method can effectively increase the period and raise the complexity of the chaotic sequences to some extent.     

单变量耦合及自适应控制统一混沌系统的同步

针对混沌系统的控制与同步问题,对统一混沌系统的同步问题进行了理论分析,基于单变量的耦合控制与自适应控制方法分别进行了同步控制器的设计和理论证明。采用单变量控制在实现同步的过程中仅需从驱动系统传递一个状态变量到响应系统用于同步,因此具有很好的实用性。仿真验证了这两种控制方法的有效性。     

Periodic performance of the chaotic spreadspectrum sequence on finite precision

It is well known that the periodic performance of spread spectrum sequence heavily affects the correlative and secure characteristics of communication systems. The chaotic binary sequence is paid more and more attention since it is one kind of applicable spread spectrum sequences. However, there are unavoidable short cyclic problems for chaotic binary sequences in finite precision. The chaotic binary sequence generating methods are studied first. Then the short cyclic behavior of the chaotic sequences is analyzed in detail, which are generated by quantification approaches with finite word-length. At the same time, a chaotic similar function is defined for presenting the cyclic characteristics of the sequences. Based on these efforts, an improved method with scrambling control for generating chaotic binary sequences is proposed. To quantitatively describe the improvement of periodic performance of the sequences, an orthogonal estimator is also defined. Some simulating results are provided. From the theoretical deduction and the experimental results, it is concluded that the proposed method can effectively increase the period and raise the complexity of the chaotic sequences to some extent.     

基于混沌序列的MIMO雷达互补相位编码波形设计

多发多收(multiple-input multiple-output,MIMO)雷达使用相互正交的波形作为发射波形。用混沌序列可以在短时间内产生任意数量、任意长度的正交混沌相位编码波形。由于互相关和自相关旁瓣的影响,混沌相位编码波形作为发射信号时的脉冲压缩输出具有较高的距离旁瓣。提出一种通过遗传算法联合迭代算法,搜索设计混沌相位编码发射波形的最优互补波形的方法,使得这种互补发射结构能够有效地抑制高脉冲压缩输出距离旁瓣,从而提高MIMO雷达的目标检测性能,特别是对相邻弱小目标的检测性能。仿真部分基于4种常用混沌序列,与相关文献中波形进行比较,证明了该方法的有效性。     

混沌时间序列建模及预测

讨论了混沌时间序列的建模及预测方法 ,给出了各重要参数的选取算法 ,并应用于实例 ,与传统的时间序列预测方法相比较 ,取得了精度更高的预测结果 ,从而为一类非线性时间序列提供了从数据采集识别到建模预测的完整技术.     

混沌时间序列的混合遗传神经网络预测方法

在相空间重构理论的基础上,将改进的遗传算法和神经网络结合起来,提出了一种混合遗传神经网络预测混沌时问序列的方法.通过复相关法和Cao方法重构混沌时间序列,利用改进的遗传算法优化神经网络的结构、初始权值和阚值,然后训练神经网络求得最优解.该算法应用到混沌时间序列的预测中,验证了该算法的有效性,并与BP和RBF算法的预测精度进行了比较,仿真结果表明该算法对混沌时间序列具有更好的非线性拟合能力和更高的预测精度.     

静态负荷模型参数辨识的一种混沌优化策略

混沌优化方法利用混沌运动的随机性、规律性、遍历性寻优,能以较大的概率搜索到全局最优点。将一种高精度的混沌优化策略用于电力系统静态负荷模型参数辨识,克服了传统的基于梯度寻优的辨识方法容易陷入局部最优点的不足。此方法使用了三步混沌搜索,并引入随机数来增强遍历性。实际算例的辨识结果证实了此方法在静态负荷模型参数辨识中的有效性和准确性。     

线性反馈及部分变量非线性反馈控制陈氏混沌同步

对陈氏混沌系统的同步问题进行了理论分析 ,并证明了线性反馈控制同步规则。基于Lyapunov函数提出了几种基于部分变量的非线性反馈控制同步规则 ,其特点是仅需对响应系统部分变量施加控制就可以实现同步 ,而且同步速度较快。仿真结果证实了几种同步规则的可行性。通过与已有控制方法的比较 ,验证了同步响应速度快的特点。     

Secure property of chaotic encryption system based on chaotic synchronization

1 .INTRODUCTIONAsanapplicationofchaostheory ,securecommunica tionshavebeenstudiedsincetheearly 1990s .Anumberofsecurecommunicationschemesbasedonchaossynchronizationareproposed .Somecryptanaly sisonthesesecuresystemsispresented [1,2 ] .Theyarebasedonpartia…