＜正＞In this paper,the problem of passivity for Hopfield neural networks with time-varying delay is investigated...
Jin Zhu~(a,b),Qiangkui Leng~c,Qingling Zhang~(a,b*) a Institute of Systems Science,Northeastern University,Shenyang,Liaoning,110004,P.R.China b Key Laboratory of Integrated Automation of Process Industry,Ministry of Education,Northeastern University,Shenyang, Liaoning,110004,P.R.China c College of Information Science and Engineering,Bohai University,Jinzhou,Liaoning,121000,P.R.China
In this article,a generalized Biological dynamical model of algal blooms is considered.The mathematical model ...
Qingling Zhang is with the Institute of system science,Northeastern University,Shenyang,China.Yugen Chang is with the Institute of system science,Northeastern University,Shenyang,China.Hong Niu is with the Institute of system science,Northeastern University,Shenyang,China.Chao Liu is with the Department of Information and Computational Science,Northeastern University at Qinhuangdao,Qinhuangdao,China.
This paper deals with the problem of synchronization for a class of uncertain chaotic systems. The uncertainties under consideration are assumed to be Lipschitz-like nonlinearity in tracking error, with unknown growth rate. A logic-based switching mechanism is presented for tracking a smooth orbit that can be a limit cycle or a chaotic orbit of another system. Based on the Lyapunov approach, the adaptation law is determined to tune the controller gain vector online according to the possible nonlinearities. To demonstrate the efficiency of the proposed scheme, the well-known chaotic system namely Chua＇s circuit is considered as an illustrative example.
The global stability problem of Takagi-Sugeno（T-S） fuzzy Hopfield neural networks（FHNNs） with time delays is investigated.Novel LMI-based stability criteria are obtained by using Lyapunov functional theory to guarantee the asymptotic stability of the FHNNs with less conservatism.Firstly,using both Finsler＇s lemma and an improved homogeneous matrix polynomial technique,and applying an affine parameter-dependent Lyapunov-Krasovskii functional,we obtain the convergent LMI-based stability criteria.Algebraic properties of the fuzzy membership functions in the unit simplex are considered in the process of stability analysis via the homogeneous matrix polynomials technique.Secondly,to further reduce the conservatism,a new right-hand-side slack variables introducing technique is also proposed in terms of LMIs,which is suitable to the homogeneous matrix polynomials setting.Finally,two illustrative examples are given to show the efficiency of the proposed approaches.
This paper studies the synchronization of complex dynamical networks constructed by spatiotemporal chaotic systems with unknown parameters. The state variables in the systems with uncertain parameters are used to construct the parameter recognizers, and the unknown parameters are identified. Uncertain spatiotemporal chaotic systems are taken as the nodes of complex dynamical networks, connection among the nodes of all the spatiotemporal chaotic systems is of nonlinear coupling. The structure of the coupling functions between the connected nodes and the control gain are obtained based on Lyapunov stability theory. It is seen that stable chaos synchronization exists in the whole network when the control gain is in a certain range. The Gray-Scott models which have spatiotemporal chaotic behaviour are taken as examples for simulation and the results show that the method is very effective.
