平移法控制离散系统的倍周期分岔和混沌

利用平移系统的方法,实现了对离散非线性动力学系统的倍周期分岔的控制和混沌吸引子不稳定周期轨道的控制.只要选择适当的平移参数,使系统平移到不同位置,就可将系统控制在不同的预期轨道.将此方法应用到Logistic映射和Henon映射中取得了很好的控制效果.     

控制离散非线性系统中不稳定不动点的一种方法

提出了控制离散非线性系统中不稳定不动点的一种新方法,同时给出了组合系数和反馈系数的先取方法.将此方法应用到Logistic映射和类Henon映射中,取得了较好的控制结果. 关键词：     

非线性映射参数辨识的离散变分方法

提出一种辨识非线性映射系统中未知参数的离散变分方法, 对以x_k+1 = F(x_k,θ)为状态控制方程的所有映射混沌系统具有通用性. 对典型的Logistic映射和Henón映射中的未知参数进行了估计, 仿真结果表明了该方法的有效性.     

预测反馈法控制双向闭环时空混沌系统的理论及实验

预测反馈控制方法可以用于控制时空混沌系统,该方法是在耦合映象格子中的每个格点处加入局部预测反馈控制器.本文以双向环形Henon耦合映象格子为例,在理论上给出了将系统控制到不稳定不动点的充分条件,并通过数值计算及电路仿真实验证实该方法的有效性.     

A method of estimating the noise level in a chaotic time series

An attempt is made in this study to estimate the noise level present in a chaotic time series. This is achieved by employing a linear least-squares method that is based on the correlation integral form obtained by Diks in 1999. The effectiveness of the method is demonstrated using five artificial chaotic time series, the Henon map, the Lorenz equation, the Duffing equation, the Rossler equation and the Chua's circuit whose dynamical characteristics are known a priori. Different levels of noise are added to the artificial chaotic time series and the estimated results indicate good performance of the proposed method. Finally, the proposed method is applied to estimate the noise level present in some real world data sets.     

演示离散混沌系统分岔图的实验方法

将模拟器件和数字器件相结合,以一维Logistic映象和二维 Henon映象为例,介绍了在电路上实现离散系统分岔图的方法,实验结果与数值计算的结果非常一致.     

Hash function based on the generalized Henon map

A new Hash function based on the generalized Henon map is proposed. We have obtained a binary sequence with excellent pseudo-random characteristics through improving the sequence generated by the generalized Henon map, and use it to construct Hash function. First we divide the message into groups, and then carry out the Xor operation between the ASCII value of each group and the binary sequence, the result can be used as the initial values of the next loop. Repeat the procedure until all the groups have been processed, and the final binary sequence is the Hash value. In the scheme, the initial values of the generalized Henon map are used as the secret key and the messages are mapped to Hash values with a designated length. Simulation results show that the proposed scheme has strong diffusion and confusion capability, good collision resistance, large key space, extreme sensitivity to message and secret key, and it is easy to be realized and extended.     

一种基于系统变量的线性和非线性变换实现混沌控制的方法

提出了一种通过系统变量的线性和非线性变换实现混沌控制的方法,以Henon映象和Lorenz系统作为两个典型的例子,验证了这种控制方法的有效性.结果表明,通过改变系统变量之间的线性变换矩阵,可以实现混沌系统中各种不稳定周期轨道的稳定控制.将这种方法推广到非线性(神经网络)变换,可以获得稳定的新的动力学行为.同时,从信息熵的角度,讨论了这种混沌控制方法的物理机制. 关键词：     

Chaos control by using Motor Maps

In this paper a new method for chaos control is proposed, consisting of an unsupervised neural network, namely a Motor Map. In particular a feedback entrainment scheme is adopted: a chaotic system with a given parameter set generates the reference trajectory for another chaotic system with different parameters to be controlled: the Motor Map is required to provide the appropriate time-varying gain value for the feedback signal. The state of the controlled system is considered as input to the Motor Map. Particular efforts have been paid to the feasibility of the implementation. Indeed, the simulations performed have been oriented to design a Motor Map suitable for an hardware realization, thus some restrictive hypotheses, such as for example a low number of neurons, have been assumed. A huge number of simulations has been carried out by considering as system to be controlled a Double Scroll Chua Attractor as well as other chaotic attractors. Several reference trajectories have also been considered: a limit cycle generated by a Chua's circuit with different parameters values, a double scroll Chua attractor, a chaotic attractor of the family of the Chua's circuit attractors. In all the simulations instead of controlling the whole state space, only two state variables have been fed back. Good results in terms of settling time (namely, the period in which the map learns the control task) and steady state errors have been obtained with a few neurons. The Motor Map based adaptive controller offers high performances, specially in the case when the reference trajectory is switched into another one. In this case, a specialization of the neurons constituting the Motor Map is observed: while a group of neurons learns the appropriate control law for a reference trajectory, another group specializes itself to control the system when the other trajectory is used as a reference. A discrete components electronic realization of the Motor Map is presented and experimental results confirming the simulation results are shown. (c) 2002 American Institute of Physics.     

Model-based detector and extraction of weak signal frequencies from chaotic data

Detecting a weak signal from chaotic time series is of general interest in science and engineering. In this work we introduce and investigate a signal detection algorithm for which chaos theory, nonlinear dynamical reconstruction techniques, neural networks, and time-frequency analysis are put together in a synergistic manner. By applying the scheme to numerical simulation and different experimental measurement data sets (Henon map, chaotic circuit, and NH(3) laser data sets), we demonstrate that weak signals hidden beneath the noise floor can be detected by using a model-based detector. Particularly, the signal frequencies can be extracted accurately in the time-frequency space. By comparing the model-based method with the standard denoising wavelet technique as well as supervised principal components analysis detector, we further show that the nonlinear dynamics and neural network-based approach performs better in extracting frequencies of weak signals hidden in chaotic time series.     

用截面映象非线性延时反馈控制混沌

提出了利用相空间Poincare截面上的非线性延时反馈稳定微分动力系统混沌吸引子中不稳定周期轨道的新方法.以Henon映象和带注入信号的双光子激光系统为例，给出了理论分析和数值模拟结果．这种方法的主要特点是不需要获取混沌系统中不稳定周期轨道的任何信息，并且可以在混沌态的任意时刻施加控制作用．     

用数字有限脉冲响应滤波器控制混沌

利用数字有限脉冲响应滤波器稳定微分动力系统和二维离散映象混沌吸引子中不稳定周期轨道的方法，实现了高周期轨道的稳定控制.分别研究了Lorenz系统和Henon映象，给出了初步的分析和数值模拟结果.这种方法的主要特点是不需要获取混沌系统中不稳定周期轨道的任何信息，控制参数的选择与被控混沌系统无关. 关键词：     

混沌的模糊神经网络逆系统控制

提出用Sugeno型的模糊推理神经网络建立混沌系统的逆系统模型,并采用逆系统方法进行混沌的控制.这种方法的特点是可以不必建立混沌系统的解析模型,通过模糊神经网络学习混沌系统的运动规律,通过学习获得的规律对混沌进行有效的控制,并且该控制方法可以控制混沌系统以一定精度跟踪连续变化的给定信号.理论分析及针对虫口模型和Henon模型仿真研究证明了该方法的有效性 关键词： 混沌 模糊神经网络 逆系统控制     

A Hybrid Domain Image Encryption Algorithm Based on Improved Henon Map

A hybrid domain image encryption algorithm is developed by integrating with improved Henon map, integer wavelet transform (IWT), bit-plane decomposition, and deoxyribonucleic acid (DNA) sequence operations. First, we improve the classical two-dimensional Henon map. The improved Henon map is called 2D-ICHM, and its chaotic performance is analyzed. Compared with some existing chaotic maps, 2D-ICHM has larger parameter space, continuous chaotic range, and more complex dynamic behavior. Second, an image encryption structure based on diffusion–scrambling–diffusion and spatial domain–frequency domain–spatial domain is proposed, which we call the double sandwich structure. In the encryption process, the diffusion and scrambling operations are performed in the spatial and frequency domains, respectively. In addition, initial values and system parameters of the 2D-ICHM are obtained by the secure hash algorithm-512 (SHA-512) hash value of the plain image and the given parameters. Consequently, the proposed algorithm is highly sensitive to plain images. Finally, simulation experiments and security analysis show that the proposed algorithm has a high level of security and strong robustness to various cryptanalytic attacks.     

基于FPGA技术的混沌加密系统研究

提出了一种基于混沌加密算法和传统加密算法的混沌加密系统, 并采用FPGA技术进行了硬件开发. 根据离散化和数字化技术, 将Henon映射和Logistic映射作离散化处理, 采用Verilog HDL语言和FPGA技术产生迭代序列, 结合传统加密算法, 基于Xilinx的FPGA开发平台进行了硬件实验研究, 并给出了该系统通过互联网上实现了文件加密和解密的通信实验, 结果显示具有网络通信的应用潜力.     

用离散混沌信号驱动实现混沌同步

提出了用离散混沌系统驱动连续混沌系统导致其同步的方法,以逻辑映象、Henon映象、Lorenz系统为例,数值地研究了这种混沌同步方法.模拟结果表明,当驱动信号的强度足够大时,可使两个连续混沌系统达到完全同步,且输出信号具有类似于白噪声的宽谱特性.同时研究了用该混沌同步方法实现保密通信的可能性. 关键词：     

离散混沌电路的实现

利用基本的电子元件和基本的电路搭建成一维Logistic离散电路和二维Henon离散电路．该电路将模拟器件和数字器件巧妙结合，电路结构简单．通过模拟实验展示了混沌运动的基本特点和规律，实验结果与理论结果一致．     

基于PSO优化LSSVM的未知模型混沌系统控制

由于混沌系统存在非线性、不确定性等特点, 常规的控制方法难以获得满意的结果. 提出一种基于PSO优化LSSVM模型参数的混沌系统控制方法. 该方法利用PSO算法的收敛速度快和全局收敛能力, 优化LSSVM模型的惩罚因子和核函数参数, 避免了人为选择参数的盲目性, 提高了LSSVM模型的预测精度. 另外, 该方法不需要被控混沌系统的解析模型, 且当测量噪声存在情况下控制仍然有效. 仿真实验结果表明了该方法的有效性和可行性. 关键词： 混沌系统控制 粒子群算法 最小二乘支持向量机     

Symbolic Dynamics and Topological Entropy of Henon Map

By using the method with which the trajectories of dissipative maps can be derived from the Hamiltonian, we study the symbolic dynamics of Henon map and its relation with the symbolic dynamics of unimodal map, and compute the topological entropy as a function of the parameter a and b. Finally, the boundary of the region where the topological entropy exists on the parameter plane is given.     

基于符号向量动力学的耦合映像格子参数估计

本文,将符号动力学推广到耦合映像格子中,以Logistic映射下耦合映像格子为研究对象,研究控制参数对符号向量序列动力学特性的影响.通过研究耦合映像格子逆函数,给出耦合映像格子的遍历条件.进一步,将给出系统初始向量,禁止字以及控制参数的符号向量序列描述方法,并最终给出基于符号向量动力学的耦合映像格子控制参数估计方法.实验结果表明,根据本文算法可以有效建立符号序列和耦合映像格子控制参数之间的对应关系,能够更好地刻画了实际模型的物理过程. 关键词： 符号向量动力学 耦合映像格子 参数估计 遍历性