Further results for robust stability of cellular neural networks with linear fractional uncertainty

A novel method is proposed for existence, uniqueness, asymptotic stability of certain and uncertain cellular neural networks with interval time-varying delays. By introducing triple-integral terms, a new Lyapunov functional is established. Without assuming the boundedness and monotonicity of activation functions, by applying homeomorphism mapping theorem, Jensen integral inequality and generalized Jensen integral inequality, new delay-dependent stability criteria are obtained with some free-weighting matrices involved. Since the results are presented in terms of linear matrix inequalities, the conditions can be solved efficiently by using the recently developed interior-point algorithm. Finally, four examples are also given to illustrate the effectiveness and less conservativeness of the proposed criteria.     

Vector Wirtinger-type inequality and the stability analysis of delayed neural network

This paper proposes some new stability criteria for a class of delayed neural networks with sector and slope restricted nonlinear neuron activation function. By using the convex express of the nonlinear neuron activation function, the original delayed neural network is transformed into a linear uncertain system. The proposed method employs an improved vector Wirtinger-type inequality for constructing a novel Lyapunov functional. Based on the Lyapunov stable theory, new delay-dependent and delay-independent stability criteria for the researched system are established in terms of linear matrix inequality technique, delay partitioning approach and characteristic root method. Three illustrative examples are presented to verify the effectiveness of the main results.     

New stability criteria for a class of neutral systems with discrete and distributed time-delays: an LMI approach

In this paper, a problem of the asymptotic stability for a class of neutral systems with multiple discrete and distributed time-delays is considered. Lyapunov stability theory is applied to guarantee the stability for the systems. New discrete-delay-independent and discrete-delay-dependent stability conditions are derived in terms of the spectral radius and linear matrix inequality. By mathematical analysis, the stability criteria are proved to be less conservative than the ones reported in the current literatures. A numerical example is given to illustrate the availability of the proposed results.     

A graph-theoretic approach to exponential stability of BAM neural networks with delays and reaction-diffusion

This paper deals with the problem of global exponential stability for bidirectional associate memory (BAM) neural networks with time-varying delays and reaction-diffusion terms. By using some inequality techniques, graph theory as well as Lyapunov stability theory, a systematic method of constructing a global Lyapunov function for BAM neural networks with time-varying delays and reaction-diffusion terms is provided. Furthermore, two different kinds of sufficient principles are derived to guarantee the exponential stability of BAM neural networks. Finally, a numerical example is carried out to demonstrate the effectiveness and applicability of the theoretical results.     

Improved stability criterion and output feedback control for discrete time-delay systems

This paper investigates the stability and stabilization for a class of linear systems with time-varying delay. We provide a new finite-sum inequality which is a powerful tool for stability analysis of time-delay systems. Applying the inequality, a new stability criterion is proposed in terms of linear matrix inequalities (LMIs). We also design a method for static output feedback (SOF) control problems which contains two parts. The first part is to find an initial values of the matrix variables. By utilizing the initial values, the condition for SOF control problems can be solved by an improved path-following method. Numerical examples demonstrate the effectiveness of the stability criterion and the SOF stabilization method.     

On periodic solutions to a class of non-autonomously delayed reaction-diffusion neural networks

In this paper, we investigate the existence and attractivity of periodic solutions for non-autonomous reaction-diffusion Cohen–Grossberg neural networks with discrete time delays. By combining the Lyapunov functional method with the contraction mapping principle and Poincaré inequality, we establish several criteria for the existence and global exponential stability of periodic solutions. More interestingly, Poincaré inequality is used to handle the reaction-diffusion terms, hence all the criteria depend on reaction-diffusion terms. These criteria are applicable in Cohen–Grossberg neural networks with both the Dirichlet and the Neumann boundary conditions on a general space domain. Several examples with numerical simulations are given to demonstrate the results.     

Remainder terms for several inequalities on some groups of Heisenberg-type

We give estimates of the remainder terms for several conformally-invariant Sobolev-type inequalities on the Heisenberg group. By considering the variations of associated functionals, we give a stability for two dual inequalities: The fractional Sobolev(FS) and Hardy-Littlewood-Sobolev(HLS) inequalities, in terms of distance to the submanifold of extremizers. Then we compare their remainder terms to improve the inequalities in another way. We also compare, in the limit case, the remainder terms of Beckner-Onofri(BO) inequality and its dual logarithmic Hardy-Littlewood-Sobolev(Log-HLS) inequality. Besides, we also list without proof some results for other groups of Iwasawa-type. Our results generalize earlier works on Euclidean spaces of Chen et al.(2013) and Dolbeault and Jankowiak(2014) onto some groups of Heisenberg-type. We worked for "almost"all fractions especially for comparing results, and the stability of HLS is also absolutely new, even for Euclidean case.     

变时滞不确定线性系统的H_\infty控制

对于一类不确定状态时变时滞系统,利用基于时滞划分的Lyapunov-Krasovskii泛函讨论其稳定性,并得到以LMI形式给出的一种保守性小的稳定性条件,最后通过分析并给出了保证系统鲁棒稳定的H_\infty控制器,数值实例表明了方法的有效性.     

时滞不确定性Markov切换线性随机微分系统的指数鲁棒稳定性

研究了一类时滞不确定性Markov切换随机微分系统的均方指数鲁棒随机稳定性\bd 系统中的时滞是时变的, 不确定项结构为范数有界, Markov切换是连续时间、离散状态的时齐Markov过程{\bf\!.} 利用随机Lyapunov函数方法和LMI技术, 得到了几个判定系统均方指数鲁棒随机稳定性的充分性条件\bd 一个数值例子说明了判据的有效性和可行性.     

Delay-dependent robust control for uncertain switched systems with time-delay

This paper considers a class of uncertain switched systems with constant time-delay. Based on Krasovskii–Lyapunov functional methods and linear matrix inequality techniques, delay-dependent stability conditions for robust stability and stabilization of the system are derived in terms of linear matrix inequalities. Moreover, dwell time constraints are imposed for the switching law. Some numerical examples are also given to illustrate the results.     

具有变时滞的离散切换系统的时滞依赖稳定性的新判据

This paper deals with the issues of robust stability for uncertain discrete-time switched systems with mode-dependent time delays.Based on a novel difference inequality and a switched Lyapunov function,new delay-dependent stability criteria are formulated in terms of linear matrix inequalities （LMIs） which are not contained in known literature.A numerical example is given to demonstrate that the proposed criteria improves some existing results significantly with much less computational effort.     

不确定变时滞系统的一个时滞相关稳定性判据

本文讨论不确定变时滞系统的稳定性问题.基于一个新的Lyapunov泛函,并利用一种新的方法处理不确定项,得到了不确定变时滞系统的一个时滞相关的稳定性判据,并利用矩阵不等式的形式给出该判据.与已有文献相比较,所得结论允许时滞导数(?)(t)(?)1且具有较少的限制条件,因此具有较弱的保守性.最后,通过两个例子验证了所给结论的正确性.     

Delay-dependent stability criterion for delayed Hopfield neural networks

In this paper, a new Lyapunov–Krasovskii functional is constructed for delayed Hopfield neural networks, and several free-weighting matrices and S-procedure are employed to derive the delay-dependent stability criterion. The derived criterion is formulated in terms of linear matrix inequality (LMI). A numerical example is given to demonstrate the effectiveness and less conservativeness of the presented criterion.     

Global robust stability for stochastic interval neural networks with continuously distributed delays of neutral type

In this paper, by using the Lyapunov-Krasovskii functional method, we investigate the global robust stability for stochastic interval neural networks with continuously distributed delays of neutral type. Some new stability criteria are presented in terms of linear matrix inequality (LMI). Two numerical examples are also given to show the effectiveness of the obtained results using LMI control toolbox in MATLAB.     

Global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms

In this paper, the global exponential stability of impulsive fuzzy cellular neural networks with mixed delays and reaction-diffusion terms is considered. By establishing an integro-differential inequality with impulsive initial condition and using the properties of M-cone and eigenspace of the spectral radius of nonnegative matrices, several new sufficient conditions are obtained to ensure the global exponential stability of the equilibrium point for fuzzy cellular neural networks with delays and reaction-diffusion terms. These results extend and improve the earlier publications. Two examples are given to illustrate the efficiency of the obtained results.     

Delay dependent stability analysis of neutral systems with mixed time-varying delays and nonlinear perturbations

This paper is concerned with the problem of stability of neutral systems with interval time-varying delays and nonlinear perturbations. The uncertainties under consideration are nonlinear time-varying parameter perturbations and norm-bounded uncertainties. A new delay-dependent stability condition is derived in terms of linear matrix inequality by constructing a new Lyapunov functional and using some integral inequalities without introducing any free-weighting matrices. Numerical examples are given to demonstrate the effectiveness and less conservativeness of the proposed methods.     

New delay-dependent robust stability criterion for uncertain neutral systems with time-varying delay and nonlinear uncertainties

This paper investigates the robust stability of uncertain neutral system with time-varying delay and nonlinear uncertainties. By using Lyapunov method and linear matrix inequality technology, a new delay-dependent stability criteria is obtained and formulated in terms of linear matrix inequalities (LMIs) which can be easy to check the robust stability of the considered systems. Numerical examples are given to indicate significant improvements over some existing results.     

Stability analysis for variational inequality in reflexive Banach spaces

This paper is devoted to the stability analysis in variational inequality. We obtain some stability results for variational inequality with both the mapping and the set that are perturbed in reflexive Banach spaces, provided that the mappings are pseudomonotone in the sense of Karamardian. The stability is also discussed for the Minty variational inequality as the mappings are properly quasimonotone. The results in this paper generalized some known results in this area.     

基于LMIs的一类不确定线性切换系统的鲁棒控制

基于LMIs处理方法,研究了一类不确定线性切换系统在任意切换下的鲁棒控制问题.利用矩阵Schur补引理构造线性矩阵不等式,得到该系统的鲁棒稳定性的充要条件,同时也给出了在状态反馈下的鲁棒稳定性充要条件和在输出反馈下的充分条件.最后用数值例子对所得结果加以验证,说明了文中结果的正确性.     

不确定随机时滞系统的时滞相关鲁棒镇定

研究一类不确定随机时滞系统的时滞相关鲁棒镇定问题.通过引入参数化的中立型模型变换,构造Lyapunov-krasovskii泛函,运用线性矩阵不等式方法,得到了使得闭环系统为均方指数稳定的保守性较小的时滞相关鲁棒镇定条件.