基于事件触发的复杂网络系统的状态估计

为减轻网络负荷,引入了基于信息采样的事件触发机制,在此基础上研究了一类具有随机节点结构的复杂网络系统的状态估计问题,其主要目的是分析和设计可靠性的状态估计器.考虑时滞对信号传输的影响,首先给出了带有时间延迟的复杂网络系统的状态估计模型,然后通过利用李雅普诺夫泛函稳定性理论和线性矩阵不等式技术,给出了在事件触发机制下系统估计误差均方渐进稳定和状态估计器存在的充分条件,最后通过数值例子验证了该方法的有效性.     

事件触发驱动的非线性系统有限时间状态估计器设计

主要研究了带有时滞的非线性系统基于事件触发的状态估计器.首先,利用事件触发机制建立系统中的状态估计器,并用Lyapunov函数使系统在有限时间内均方有界.其次,基于H_∞有界条件,得到了有限时间内系统H_∞有界准则.最后,通过一个数值例子说明了所得结果的有效性.     

事件触发下混合时滞神经网络的状态估计

研究了事件触发机制下混合时滞神经网络的状态估计问题.通过引入依赖于测量输出且具有指数衰减特性的阈值函数,设计了新的事件触发机制来降低采样和通信频率.综合混合时延和事件触发特性,建立了新的状态估计误差系统.采用Lyapunov函数和不等式技术,建立了误差系统指数稳定性条件,分析并排除了事件触发机制中的Zeno现象.最后通过例子验证了理论方法的有效性.     

基于事件触发控制带有多时变时滞的主从系统同步

研究了基于事件触发机制下带有多个时变时滞的主从系统同步问题.事件触发机制的提出,使得在实现主从系统同步的过程中,可以有效降低数据传输量,减轻网络带宽的压力.通过Lyapunov稳定理论和线性矩阵不等式的方法,得到了带有多时变时滞的主从系统同步的充分条件.最后,通过MATLAB仿真,验证了所提出同步准则的有效性.     

合同下矩阵特征值与T合同下矩阵奇异值的估计

本文讨论了 *合同下 Hermite矩阵的诸特征值及 T合同下对称矩阵 (实或复 )的诸奇异值的变化情况 ,给出的结果改进了 Sylvester,Ostrowski[1] 等人的相应结果 .另外 ,本文还得到了两 Hermite矩阵乘积的特征值和两复矩阵乘积的奇异值的估计 ,改进并推广了 Sha Huyn[3 ] 、郁易生[4 ] 、周金士[5] 等人的结果     

事件触发下多智能体系统规定时间二分一致性

针对线性合作竞争多智能体系统(MAS),考虑到可能受到的外部干扰,研究了系统基于事件触发机制的规定时间二分一致性控制问题.首先,设计干扰观测器估计系统受到的外部干扰,且针对每个智能体给出了事件触发条件,以减少智能体间的通信频率,节省有限的通信网络资源,同时证明避免了Zeno现象,其次,为了明确地预先分配稳定时间,结合干扰观测器的估计值,设计了一种合作和竞争并存拓扑结构的规定时间事件触发控制协议,以保证所有智能体在受到外部干扰的情况下仍然达到二分一致.最后,利用仿真实例验证了所提出方法的可行性和有效性.     

基于事件触发的时滞Lur’e系统主从同步研究

研究了基于事件触发采样控制的时滞混沌Lur’e系统主从同步问题.首先考虑了系统中包含的传输时滞构造了系统时滞模型.然后,通过构造三重积分项的Lyapunov-Krasovskii泛函,并结合Wirtinger积分不等式和凸组合技术对Lyapunov-Krasovskii泛函的导数进行估计,给出了混沌系统主从同步的充分条件.所提出的事件触发机制应用于主从同步研究中,可以有效地减少采样数据传输,缓解网络带宽压力,提高网络带宽利用率.最后,通过时滞蔡氏电路的数值仿真,验证了所提出同步准则的有效性.     

复矩阵截断奇异值分解的一类混合算法

截断奇异值分解是一类非常重要的矩阵分解,其在病态模型问题分析等领域有广泛的应用.该文主要研究复矩阵截断奇异值分解的有效算法,将问题转化为复Stiefel乘积流形上的黎曼优化问题,进而设计基于乘积流形的黎曼混合牛顿法求解.为有效求解黎曼牛顿方程,从降低系统维数和简化计算入手,通过克罗内克积和复矩阵拉直算子将其转化为易于求解的标准实对称线性方程组.数值实验和数值比较验证该文所提算法针对复矩阵截断奇异值分解问题是高效可行的.     

关于复正定矩阵乘积迹的估计

讨论了复正定矩阵乘积迹的估计式 ,得到了一系列估计复正定矩阵乘积迹的不等式     

关于复正定矩阵行列式的不等式

本文讨论了复正定矩阵行列式的估计式 ,修正了文 [2 ]的一些错误 ,得到了一些复正定矩阵行列式的不等式 .     

Multiplicative Maps With Specified (1, 1)-Entry

In this article, we will show that for many complex-valued maps f over a semigroup G of matrices, there exists a minimum k for the existence of a multiplicative map for which the (1, 1)-entry of } ( A ) is f ( A ). We obtain results on such multiplicative maps, and use them to classify all the multiplicative maps on G such that f ( A ) = ( g ( A )) for any A k G , where f and g are given complex-valued maps.     

Complex symmetric matrices with strongly stable iterates

We study complex-valued symmetric matrices. A simple expression for the spectral norm of such matrices is obtained, by utilizing a unitarily congruent invariant form. Consequently, we provide a sharp criterion for identifying those symmetric matrices whose spectral norm does not exceed one: such strongly stable matrices are usually sought in connection with convergent difference approximations to partial differential equations. As an example, we apply the derived criterion to conclude the strong stability of a Lax-Wendroff scheme.     

An inverse spectral problem for complex Jacobi matrices

We introduce the concept of generalized spectral function for finite order complex Jacobi matrices and solve the inverse problem with respect to the generalized spectral function. The results obtained can be used for solving of initial-boundary value problems for finite nonlinear Toda lattices with the complex-valued initial conditions by means of the inverse spectral problem method.     

Multiplicative Maps With Specified (1, 1)-Entry

In this article, we will show that for many complex-valued maps f over a semigroup G of matrices, there exists a minimum k for the existence of a multiplicative map for which the (1, 1)-entry of ϕ( A ) is f ( A ). We obtain results on such multiplicative maps, and use them to classify all the multiplicative maps τon G such that f ( A ) = τ( g ( A )) for any A ε G , where f and g are given complex-valued maps.     

A note on maximum likelihood estimation for the complex-valued first-order autoregressive process

The maximum likelihood estimation of the parameters of a complex-valued zero-mean normal stationary first-order autoregressive process is investigated. It is shown that the likelihood function corresponding to independent replicated series is uniquely maximized at a point in the interior of the parameter space. A closed-form expression is given for the estimator.     

时间标度上时滞脉冲复值神经网络的全局稳定性

研究了时间标度上具有时滞和脉冲影响的复值神经网络的全局稳定性问题.利用时间标度上的微积分理论,将连续时间型复值神经网络和离散时间型复值神经网络统一在同一个框架下进行研究.在不要求激励函数有界的条件下,运用同胚映射原理,建立了确保时滞复值神经网络平衡点存在性和唯一性的判定条件.通过构造合适的Lyapunov-Krasovskii泛函,并使用自由权矩阵方法和矩阵不等式技巧,获得了时间标度上具有时滞和脉冲影响的复值神经网络平衡点全局稳定性的充分条件.给出的判据是由复值线性矩阵表示的,易于MATLAB软件的YALMIP Toolbox实现.数值仿真实例验证了获得结果的有效性.     

A real-valued block conjugate gradient type method for solving complex symmetric linear systems with multiple right-hand sides

We consider solving complex symmetric linear systems with multiple right-hand sides. We assume that the coefficient matrix has indefinite real part and positive definite imaginary part. We propose a new block conjugate gradient type method based on the Schur complement of a certain 2-by-2 real block form. The algorithm of the proposed method consists of building blocks that involve only real arithmetic with real symmetric matrices of the original size. We also present the convergence property of the proposed method and an efficient algorithmic implementation. In numerical experiments, we compare our method to a complex-valued direct solver, and a preconditioned and nonpreconditioned block Krylov method that uses complex arithmetic.     

具有混合时滞的脉冲复值神经网络的全局μ-稳定性

研究了具有离散变化时滞和无界分布时滞的脉冲复值神经网络的稳定性,在所研究的神经网络中,活动函数仅仅要求满足Lipschitz条件.运用同胚映射原理,证明了具有混合时滞的脉冲复值神经网络平衡点的存在性和唯一性.通过构造Lyapunov-Krasovskii泛函,使用自由权矩阵方法和不等式技巧,获得了网络平衡点的全局μ-稳定性的充分性判据.数值仿真实例验证了结果的有效性.     

具有反应扩散项的变时滞复数域神经网络的指数稳定性

该文研究了一类具有反应扩散项的变时滞复数域神经网络的指数稳定性.首先在假设复数域激活函数可分解的情况下,将该系统分解为相应的实部系统和虚部系统.利用矢量Lyapunov函数法和M矩阵理论,得到了确保该系统平衡状态指数稳定性的充分条件.该条件不含有任何自由变量,相对现有结论具有较低的保守性.最后通过一个数值仿真算例验证了所得结论的正确性.     

Operational matrices of Chebyshev cardinal functions and their application for solving delay differential equations arising in electrodynamics with error estimation

In this paper, a new and effective direct method to determine the numerical solution of pantograph equation, pantograph equation with neutral term and Multiple-delay Volterra integral equation with large domain is proposed. The pantograph equation is a delay differential equation which arises in quite different fields of pure and applied mathematics, such as number theory, dynamical systems, probability, mechanics and electrodynamics. The method consists of expanding the required approximate solution as the elements of Chebyshev cardinal functions. The operational matrices for the integration, product and delay of the Chebyshev cardinal functions are presented. A general procedure for forming these matrices is given. These matrices play an important role in modelling of problems. By using these operational matrices together, a pantograph equation can be transformed to a system of algebraic equations. An efficient error estimation for the Chebyshev cardinal method is also introduced. Some examples are given to demonstrate the validity and applicability of the method and a comparison is made with existing results.