Uniform asymptotic stability for perturbed neutral delay differential equations

One-dimensional perturbed neutral delay differential equations of the form (x(t)−P(t,x(t−τ)))′=f(t,x_t)+g(t,x_t) are considered assuming that f satisfies −v(t)M(φ)?f(t,φ)?v(t)M(−φ), where M(φ)=max{0,max_s∈[−r,0]φ(s)}. A typical result is the following: if ‖g(t,φ)‖?w(t)‖φ‖ and , then the zero solution is uniformly asymptotically stable providing that the zero solution of the corresponding equation without perturbation (x(t)−P(t,x(t−τ)))′=f(t,x_t) is uniformly asymptotically stable. Some known results associated with this equation are extended and improved.     

���ڸ�ά���ݵĸ���Hotelling'sT-square ����

The paper is concerned with the two-sample meantesting problem in high-dimension settings. We propose a composite Hotelling'sT-square test, establish its asymptotical normality and study its local power.The finite-sample priority of the proposed test over existing high-dimensionaltests is shown by simulations and illustrated by a real data-set analysis.     

PDα‐type distributed learning control for nonlinear fractional‐order multiagent systems

This paper considers the consensus tacking problem for nonlinear fractional‐order multiagent systems by presenting a PD^α‐type iterative learning control update law with initial learning mechanisms. The asymptotical convergence of the proposed distributed learning algorithm is strictly proved by using the properties of fractional calculus. A sufficient condition is derived to guarantee the whole multiagent system achieving an asymptotic output consensus. An illustrative example is given to verify the theoretical results.     

Periodic solution of a chemostat model with variable yield and impulsive state feedback control

In this paper, a chemostat model with variable yield and impulsive state feedback control is considered. We obtain sufficient conditions of the globally asymptotical stability of the system without impulsive state feedback control. We also obtain that the system with impulsive state feedback control has periodic solution of order one. Sufficient conditions for existence and stability of periodic solution of order one are given. In some cases, it is possible that the system exists periodic solution of order two. Our results show that the control measure is effective and reliable.     

一类带有不育控制的离散单种群模型

建立一类不育控制下的害鼠种群的离散模型.首先利用三个Jury条件,得到平衡点的局部渐近稳定性的充分条件.其次利用李雅普诺夫函数和细致分析法分别给出了零平衡点全局稳定及持续生存的充分条件.最后给出了平衡点全局稳定的数值模拟.     

ASYMPTOTICAL STABILITY OF NON-AUTONOMOUS DISCRETE-TIME NEURAL NETWORKS WITH GENERALIZED INPUT-OUTPUT FUNCTION

In this paper, we first introduce the model of discrete-time neural networkswith generalized input--output function and present a proof of the existence of afixed point by Schauder fixed-point principle. Secondly, we study the uniformlyasymptotical stability of equilibrium in non-autonomous discrete--time neuralnetworks and give some sufficient conditions that guarantee the stability of itby using the converse theorem of Lyapunov function. Finally, several examplesand numerical simulations are given to illustrate and reinforce our theories.     

Sequential estimation of the minimum of a random variable

The paper presents a sequential method of fixed-width asymptotically consistent estimation of the minimal value μ of a random variable in the sense μ = inf{ x: F(x) > 0} where F is a distribution function of the considered variable. The theory of extremal order statistics is used.     

单向分类随机效应模型中方差分量的渐近最优经验Bayes估计

本文在加权平方损失下导出了单向分类随机效应模型中方差分量的Bayes估计, 利用多元密度及其偏导数的核估计方法构造了方差分量的经验Bayes(EB)估计,证明了 EB估计的渐近最优性.文末还给出了一个例子说明了符合定理条件的先验分布是存在 的.     

遥操作系统的稳定性与透明性分析

遥操作机器人系统的通信通道中存在通信时延,而且机器人模型存在不确定性,以致可能造成系统不稳定和操作性能降低.针对通信时延和系统不确定性,利用鲁棒控制理论,提出用力、位置和速度反馈的控制方法,使得系统稳定,且具有良好的透明性.仿真结果表明了该方法的有效性.     

Chaos and asymptotical stability in discrete-time recurrent neural networks with generalized input-output function

We theoretically investigate the asymptotical stability, local bifurcations and chaos of discrete-time recurrent neural networks with the form of