分离变量非线性系统的全局稳定性

借助Lyapunov函数方法 ,讨论了一类分离变量系统的全局稳定性和全局指数稳定性 ,得到了由系统自身特点所给出的几个显示代数判据 ,这些充分性结论为实际应用提供方便 ,推广了有关文献中的一些结果 .     

General hybrid projective complete dislocated synchronization with non-derivative and derivative coupling based on parameter identification in several chaotic and hyperchaotic systems

According to the Lyapunov stability theorem, a new general hybrid projective complete dislocated synchronization scheme with non-derivative and derivative coupling based on parameter identification is proposed under the framework of drive-response systems. Every state variable of the response system equals the summation of the hybrid drive systems in the previous hybrid synchronization. However, every state variable of the drive system equals the summation of the hybrid response systems while evolving with time in our method. Complete synchronization, hybrid dislocated synchronization, projective synchronization, non-derivative and derivative coupling, and parameter identification are included as its special item. The Lorenz chaotic system, Rssler chaotic system, memristor chaotic oscillator system, and hyperchaotic Lü system are discussed to show the effectiveness of the proposed methods.     

离散代数Riccati方程解的上下界

给出离散代数Ｒｉｃｃａｔｉ方程解的迹的上界和下界计算公式,较现有结果相比,该结果具有较高的估计精度,数值算例表明该方法的有效性。     

Banach空间无界时滞的脉冲发展中立泛函积分微分包含的存在性

本文建立了Banach空间中无界时滞的脉冲发展中立泛函积分微分包含温和解存在的充分条件，我们利用由Dhage建立的多值混合不动点定理与发展系统证明了解的存在性．     

基于规范高阶累积量的盲分离算法

本文给出信号的r阶规范累积量定义,证明了在信号瞬时线性混叠情况下r阶规范累积量绝对值不超过最大源信号的r阶规范累积量,因此可以通过最大化r阶规范累积量的绝对值实现盲分离.最大化r阶规范累积量的绝对值可以得到两种盲分离算法,一种高效快速算法———特征值分解盲分离算法,另外一种盲提取算法.本文为高阶累积量盲分离奠定了严格的理论基础.仿真结果验证了理论的正确性和算法的有效性.     

ASYMPTOTIC STABILITIES OF STOCHASTIC FUNCTIONAL DIFFERENTIAL EQUATIONS

Asymptotic characteristic of solution of the stochastic functional differential equation was discussed and sufficient condition was established by multiple Lyapunov functions for locating the limit set of the solution. Moreover, from them many effective criteria on stochastic asymptotic stability, which enable us to construct the Lyapunov functions much more easily in application, were obtained. The results show that the well-known classical theorem on stochastic asymptotic stability is a special case of our more general results. In the end, application in stochastic Hopfield neural networks is given to verify our results.     

Robust Stabilization Analysis for Uncertain Systems with Time-Varying Delays

Many techniques have been proposed to stabilize uncertain systems with state delay via state feedback in Ref.[1~12], LI et al. investigated the approach of linear matrix inequality (LMI) [1,5], Mori, Su et al. discussed the robust stabilization where the uncertainty satisfies the so-called matching conditions, by using the property of LMI[2,3]. Perterson et al. introduced a Ricatti equation approach[6], Hoi, Shen et al., designed the state feedback controller to stabilize the uncertain dy…     

广义的时滞细胞神经网络的动态分析

本文研究了广义细胞神经网络的动态行为,首先利用度理论建立了客中广义时滞细胞神经网络的平衡点存在唯一物充要条件,其次给出这种广义时滞神经网络全局指数稳定的充要条件。     

Hopfield型时滞神经网络的指数稳定性

研究了Ｈｏｐｆｉｅｌｄ型随机时滞神经网络ｄｘ（ｔ）＝［－Ａｘ（ｔ）＋Ｂσ（ｘ（ｔ一τ））］ｄｔ＋ｆ（ｔ．ｘ（ｔ）,Ｘ（ｔ—τ））ｄｗ（ｔ）的均方指数稳定性与几乎必然指数稳定性．应用Ｌａｙａｐｕｎｏｖ函数与鞅不等式,建立了这种随机时滞神经网络指数稳定的时滞相关的充分条件．文献中某些关于确定性的时滞神经网络ｘ（ｔ）＝－Ａｘ（ｔ）＋Ｂσ（ｘ（ｔ－τ））与神经网络ｘ（ｔ）＝－Ａｘ（ｔ）＋Ｂσ（ｘ（ｔ））的稳定准则是文中的特殊情况．     

多时滞神经网络的全局指数稳定性

多时滞神经网络是一种特殊结构的动力系统,其全局指数稳定性在实际应用中起着非常重要的作用.本文通过构建Lyapunov函数的方法,对一类一般多时滞神经网络的全局指数稳定进行了分析,得到了多时滞神经网络全局指数稳定性的几个充分条件,本文的结果涵盖并推广了最近文献的结论,并给出实例进行数字仿真说明本文结果的有效性.