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We propose a novel technique for investigating the synchronization effect for uncertain networks with quantum chaotic behaviors in this paper. Through designing a special function to construct Lyapunov function of network and the adaptive laws of uncertain parameters, the synchronization between the uncertain network and the synchronization target can be realized, and the uncertain parameters in state equations of the network nodes are perfectly identified. All the theoretical results are verified by numerical simulations to demonstrate the effectiveness of the proposed synchronization technique. [ABSTRACT FROM AUTHOR]

Synchronization between uncertain nonidentical networks with quantum chaotic behavior is researched. The identification laws of unknown parameters in state equations of network nodes, the adaptive laws of configuration matrix elements and outer coupling strengths are determined based on Lyapunov theorem. The conditions of realizing synchronization between uncertain nonidentical networks are discussed and obtained. Further, Jaynes–Cummings model in physics are taken as the nodes of two networks and simulation results show that the synchronization performance between networks is very stable. [ABSTRACT FROM AUTHOR]

In this article, the absolute stability problem is investigated for Lur'e systems with time-varying delay and sector-bounded nonlinearity. By employing the delay fractioning idea, the new augmented Lyapunov functional is first constructed. Then, by introducing some slack matrices and by reserving the useful term when estimating the upper bound of the derivative of Lyapunov functional, the new delay-dependent absolute stability criteria are derived in terms of linear matrix inequalities. Several numerical examples are presented to show the effectiveness and the less conservativeness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: In this paper, the anti-synchronization of two different chaotic systems is investigated. On the basis of a nonlinear control scheme and Lyapunov theory, sufficient conditions for the stability of the error dynamics are derived, where the controllers are designed by using the sum of the relevant variables in chaotic systems. Numerical simulations are performed for the Genesio–Rossler system to demonstrate the effectiveness of the proposed control strategy. [Copyright &y& Elsevier]

Abstract: In this paper, the state estimation problem is investigated for continuous-time neural networks with time-varying delay through available output measurements. By constructing more effective Lyapunov functionals, and combining with Jensen integral inequality or free-weighting matrix approach, several less conservative sufficient conditions for the existence of state estimator are derived in terms of linear matrix inequalities (LMIs). Finally, a numerical example is presented to demonstrate the effectiveness and the reduced conservatism of proposed results. [Copyright &y& Elsevier]

Abstract: This paper considers the stability analysis problem for neural networks with time-varying delay. Firstly, the new augmented Lyapunov functional is constructed by employing the more general decomposition approach. Then based on the Lyapunov stability theory and free weight matrix method, the novel delay-dependent stability condition is derived in terms of linear matrix inequalities (LMIs). Numerical examples show that the proposed method is more effective than some existing ones. [Copyright &y& Elsevier]