一类不确定延迟神经网络的自适应投影同步

研究了一类参数不确定的延迟神经网络的投影同步,基于Lyapunov稳定性理论,设计了一种新型的自适应控制方法.该方法能同时实现一类参数不确定延迟神经网络的参数识别和投影同步.数值模拟证明了该方法的有效性. 关键词： 延迟神经网络 Lyapunov稳定性理论 参数识别 投影同步     

一类混沌神经网络的全局同步

研究了一类时滞混沌神经网络的全局同步问题.应用驱动-响应同步方法和线性矩阵不等式技术，给出了时滞混沌神经网络全局同步的充分条件和同步控制器设计方法，而且所得到的控制器易于实现.仿真示例验证了本文方法的有效性. 关键词： 混沌神经网络 同步 驱动-响应法 线性矩阵不等式     

混沌时滞神经网络系统的反同步

利用状态观测器方法研究了一类带时滞的混沌神经网络系统的反同步问题.与应用于其他混沌系统的反同步方法相比,提出的方法更为简便,并且利用极点配置技术,只要通过调整特征值来实现反同步速率的快慢.最后,给出了数值例子和计算机仿真结果来验证该方案的有效性. 关键词： 混沌神经网络 状态观测器 极点配置技术 反同步     

一类参数不确定混沌系统的延迟同步

针对一类混沌系统，研究了参数未知的混沌系统的延迟同步.基于Lyapunov稳定性定理，给出了延迟同步控制器和参数自适应律的解析表达式.该方法简单、适用范围广.以新混沌系统为例，数值模拟说明了该方法的有效性和可行性.通过研究有界噪声作用下该系统的控制效果，表明了该方法具有较强的鲁棒性和抗干扰能力. 关键词： 延迟同步 Lyapunov稳定性定理 新混沌系统 有界噪声     

基于主动滑模控制的一类混沌系统异结构反同步

针对一类连续时间混沌系统,基于主动控制思想,提出了一种主动滑模控制策略,使得一类混沌系统可以达到异结构反同步,其中响应系统的线性部分和控制器参数决定闭环误差及反同步的趋近律. 基于Lyapunov稳定性理论分析了系统的稳定性. 以Lorenz系统、Chen系统和Lü系统为例进行仿真验证,该控制方法可以实现较快的混沌反同步,且反同步的鲁棒稳定性良好. 关键词： 混沌系统 反同步 滑模控制 主动控制     

不同结构混沌系统的自适应同步和反同步

针对不同结构混沌系统的同步与反同步问题进行了研究.在系统参数已知时,采用主动控制法实现混沌系统的同步与反同步,并将主动控制器的设计方法进行了推广.在参数未知时,基于Lyapunov稳定性理论和自适应控制方法,给出了自适应控制器和参数自适应律,实现了参数均未知且结构不同的驱动系统和响应系统的同步与反同步.在控制器的设计过程中,将驱动系统和响应系统进行互换,讨论了互换前后的控制器和自适应律之间的关系.数值仿真结果说明了所提出设计方法的有效性. 关键词： 混沌同步 反同步 主动控制法 自适应控制法     

不确定自催化反应扩散时空混沌系统的延时同步

设计了一种延迟同步控制器实现了时空混沌系统之间的同步控制.基于Lyapunov稳定性定理,确定了延迟同步控制器的结构以及系统状态变量之间的误差方程.以自催化反应扩散时空混沌系统为例,仿真模拟验证了该控制器的有效性.进一步设计了参量辨识器,对不确定自催化反应扩散时空混沌系统中的参量进行了有效辨识.通过研究有界噪声影响下系统的同步效果,表明该同步方法具有较好的抗干扰能力. 关键词： 时空混沌 延时同步 参量辨识 有界噪声     

参数未知的统一超混沌系统自适应反同步

文章研究了参数未知的统一超混沌系统的控制与同步问题.首先基于Lyapunov稳定性理论,设计了自适应控制器,证明了该控制器可使参数未知统一超混沌系统渐近稳定于不动点.其次使用自适应反同步方法,设计了自适应同步控制器,实现了参数未知统一超混沌系统的完全同步,最后数值仿真实验进一步验证了所提出方案的有效性. 关键词： 统一超混沌系统 自适应控制器 自适应反同步     

时滞惯性神经网络的稳定性和分岔控制

针对一类二阶时滞惯性神经网络模型,提出一种基于时滞反馈的分岔控制方法.利用时滞微分方程动力学理论,给出反馈控制系统的稳定性以及发生Hopf分岔的判别条件.数值仿真显示所设计的控制器不仅能有效延迟网络分岔的发生,还能扩大稳定域并改善网络的收敛速度.     

基于混沌粒子群优化算法的异结构混沌反同步自抗扰控制

针对一类连续时间异结构混沌系统, 利用自抗扰控制很强的鲁棒性, 提出了一种异结构混沌系统反同步的自抗扰控制策略.针对所设计的自抗扰控制器参数较多, 难以整定的问题, 提出了应用混沌粒子群优化算法对控制器进行参数寻优设计. 以Lorenz系统和Chua系统两个异结构混沌系统为例进行仿真验证, 由仿真结果可知, 该方法可以实现异结构混沌系统较快的反同步控制, 且具有很强的抗干扰能力. 关键词： 异结构混沌系统反同步 自抗扰控制器 混沌粒子群优化算法 参数寻优     

Robust anti-synchronization of a class of delayed chaotic neural networks

This paper deals with the anti-synchronization problem of a class of delayed neural networks. Based on the Lyapunov stability theory and the Halanay inequality lemma, a kind of controller is designed. It is proved that this kind of controller can achieve anti-synchronization of neural networks with delays. Numerical simulations demonstrate the effectiveness and robustness of the proposed anti-synchronization scheme.     

Anti-synchronization of Time-delayed Chaotic Neural Networks Based on Adaptive Control

This paper investigates the adaptive anti-synchronization problem for time-delayed chaotic neural networks with unknown parameters. Based on Lyapunov-Krasovskii stability theory and linear matrix inequality (LMI) approach, the adaptive anti-synchronization controller is designed and an analytic expression of the controller with its adaptive laws of unknown parameters is shown. The proposed controller can be obtained by solving the LMI problem. An illustrative example is given to demonstrate the effectiveness of the proposed method.     

Anti-synchronization Between Two Coupled Networks with Unknown Parameters Using Adaptive and Pinning Controls

In this paper, we study anti-synchronization between two coupled networks where the node dynamics has an unknown system parameter. By designing adaptive and pinning control schemes, we realize the anti-synchronization.By Lyapunov stability theory, we obtain two theorems on the appearance of anti-synchronization. In addition, we derive a criterion for the pinning number of nodes. Finally we provide two numerical examples to show the effectiveness of our proposed control schemes. When the anti-synchronization is achieved, we successfully identify the unknown system parameter.     

Outer Synchronization of Complex Networks by Impulse

This paper investigates outer synchronization of complex networks, especially, outer complete synchronization and outer anti-synchronization between the driving network and the response network. Employing the impulsive control method which is uncontinuous, simple, efficient, low-cost and easy to implement in practical applications, we obtain some sufficient conditions of outer complete synchronization and outer anti-synchronization between two complex networks. Numerical simulations demonstrate the effectiveness of the proposed impulsive control scheme.     

Anti-synchronization Between Coupled Networks with Two Active Forms

This paper studies anti-synchronization and its control between two coupled networks with nonlinear signal's connection and the inter-network actions. If anti-synchronization does not exist between two such networks, adaptive controllers are designed to anti-synchronize them. Different node dynamics and nonidentical topological structures are considered and useful criteria foranti-synchronization between two networks are given. Numerical examples are presented to show the efficiency of our derived results.     

非线性耦合时空混沌系统的反同步研究

利用非线性耦合方法研究了离散型时空混沌系统的反同步问题.对时空混沌系统的线性项和非线性项进行适当的分离,利用系统本身的非线性项作为耦合函数,实现了两个二维耦合映象格子的反同步.进一步将这种非线性耦合方法推广应用到由二维耦合映象格子构成复杂网络的反同步研究中,仿真模拟发现仍具有理想的反同步效果. 关键词： 反同步 非线性耦合 耦合映象格子 复杂网络     

混沌神经网络的延时反馈控制研究

针对混沌神经网络，提出了一种改进的延时反馈控制方法. 利用该方法，当延时参数τ为奇数时，被控神经网络收敛于记忆模式以及它的反相模式的2周期上. 若选取不同的延时参数，被控网络则收敛于不同的周期态上. 关键词： 控制混沌 延时反馈控制 混沌神经网络     

Multistability of delayed complex-valued recurrent neural networks with discontinuous real-imaginarytype activation functions

In this paper, the multistability issue is discussed for delayed complex-valued recurrent neural networks with discontinuous real-imaginary-type activation functions. Based on a fixed theorem and stability definition, sufficient criteria are established for the existence and stability of multiple equilibria of complex-valued recurrent neural networks. The number of stable equilibria is larger than that of real-valued recurrent neural networks, which can be used to achieve high-capacity associative memories. One numerical example is provided to show the effectiveness and superiority of the presented results.     

The antisynchronization of a class of chaotic delayed neural networks

In this paper, the antisynchronization problems of a class of chaotic delayed neural networks are investigated. Some criteria of the antisynchronization of the chaotic delayed neural networks are established by using the linear matrix inequality and Lyapunov stability theory. These criteria not only improve and generalize some known results, but are also some less conservative conditions. Finally, two numerical examples and the corresponding numerical simulations are used to illustrate the effectiveness of the obtained results.