Complex networks are important paradigms for analyzing the complex systems as they allow understanding the structural properties of systems composed of different interacting entities. In this work we propose a reliabl...Complex networks are important paradigms for analyzing the complex systems as they allow understanding the structural properties of systems composed of different interacting entities. In this work we propose a reliable method for constructing complex networks from chaotic time series. We first estimate the covariance matrices, then a geodesic-based distance between the covariance matrices is introduced. Consequently the network can be constructed on a Riemannian manifold where the nodes and edges correspond to the covariance matrix and geodesic-based distance, respectively. The proposed method provides us with an intrinsic geometry viewpoint to understand the time series.展开更多
This paper is concerned with the existence of adaptive generalized synchronization(GS) of two chaotic systems.An adaptive control is designed based on a Lyapunov approach.By using modified system approach,some suffici...This paper is concerned with the existence of adaptive generalized synchronization(GS) of two chaotic systems.An adaptive control is designed based on a Lyapunov approach.By using modified system approach,some sufficient conditions for the existence of first two types of adaptive GS inertial manifolds are established.Finally,some numerical simulations are provided to illustrate the theoretical results.展开更多
基金Supported by the National Natural Science Foundation of China under Grant No 61362024
文摘Complex networks are important paradigms for analyzing the complex systems as they allow understanding the structural properties of systems composed of different interacting entities. In this work we propose a reliable method for constructing complex networks from chaotic time series. We first estimate the covariance matrices, then a geodesic-based distance between the covariance matrices is introduced. Consequently the network can be constructed on a Riemannian manifold where the nodes and edges correspond to the covariance matrix and geodesic-based distance, respectively. The proposed method provides us with an intrinsic geometry viewpoint to understand the time series.
文摘This paper is concerned with the existence of adaptive generalized synchronization(GS) of two chaotic systems.An adaptive control is designed based on a Lyapunov approach.By using modified system approach,some sufficient conditions for the existence of first two types of adaptive GS inertial manifolds are established.Finally,some numerical simulations are provided to illustrate the theoretical results.
