时变时滞耦合两个不同复杂网络的自适应广义同步

针对具有时变时滞耦合的两个不同复杂网络, 研究其广义同步问题. 基于Barbalat引理, 设计非线性自适应控制器使得两个网络获得广义同步. 进一步研究了具有未知拓扑结构的两个网络的广义同步问题. 数值仿真表明了本文方法的有效性.     

不同超混沌系统的自适应修正函数投影

研究了具有未知参数的Lorenz-Stenflo(LS)系统和一种新型超混沌系统以及LS系统和超混沌Chen系统的修正函数投影同步问题.利用Lyapunov稳定性理论和主动控制方法,设计自适应控制器和参数更新规则,实现不同超混沌系统的修正函数投影同步,同时估计出系统的未知参数.数值仿真验证了该自适应控制器的有效性.     

Pinning sampled-data synchronization for complex networks with probabilistic coupling delay

We deal with the problem of pinning sampled-data synchronization for a complex network with probabilistic time-varying coupling delay. The sampling period considered here is assumed to be less than a given bound. Without using the Kronecker product, a new synchronization error system is constructed by using the property of the random variable and input delay approach. Based on the Lyapunov theory, a delay-dependent pinning sampled-data synchronization criterion is derived in terms of linear matrix inequalities （LMIs） that can be solved effectively by using MATLAB LMI toolbox. Numerical examples are provided to demonstrate the effectiveness of the proposed scheme.     

Effects of orientation of substrate on the enhanced low-dose-rate sensitivity （ELDRS） in NPN transistors

The radiation effects and annealing characteristics of two types of domestic NPN bipolar junction transistors, fabricated with different orientations, were investigated under different dose-rate irradiation. The experimental results show that both types of the NPN transistors exhibit remarkable Enhanced Low-Dose-Rate Sensitivity (ELDRS). After irradiation at high or low dose rate, the excess base current of NPN transistors obviously increased, and the current gain would degrade rapidly. Moreover, the decrease of collector current was also observed. The NPN transistor with <111> orientation was more sensitive to ionizing radiation than that with <100> orientation. The underlying mechanisms of various experimental phenomena are discussed in detail in this paper.     

Novel delay-dependent stability criteria for neural networks with interval time-varying delay

The problem of delay-dependent asymptotic stability for neural networks with interval time-varying delay is investigated. Based on the idea of delay decomposition method, a new type of Lyapunov-Krasovskii functional is constructed. Several novel delay-dependent stability criteria are presented in terms of linear matrix inequality by using the Jensen integral inequality and a new convex combination technique. Numerical examples are given to demonstrate that the proposed method is effective and less conservative.     

不同超混沌系统的自适应修正函数投影

研究了具有未知参数的Lorenz-Stenflo(LS)系统和一种新型超混沌系统以及LS系统和超混沌Chen系统的修正函数投影同步问题.利用Lyapunov稳定性理论和主动控制方法,设计自适应控制器和参数更新规则,实现不同超混沌系统的修正函数投影同步,同时估计出系统的未知参数.数值仿真验证了该自适应控制器的有效性.     

Adaptive Synchronization of an Array of Time-Varying Coupled Delayed Neural Networks

Synchronization in an array of time-varying coupled delayed neural networks is investigated. We assume that the entries of time-varying coupling configuration matrix and inner-coupling matrix of the model are all bounded. By combining linear feedback with an adaptive control approach, some simple controllers are proposed to ensure the states of such coupled networks globally asymptotically synchronize to a desired synchronous solution. Simulation results are provided to demonstrate the effectiveness of the proposed approach.