2,312 publications from this institution
In this paper, we consider the realizability problem of n-port resistive networks containing 2n terminals. A necessary and sufficient condition for any real symmetric matrix to be realizable as the admittance of an n-port resistive network containing 2n terminals is obtained. The condition is based on the existence of a parameter matrix. We then focus on a three-port resistive network containing six terminals. A necessary and sufficient condition is derived for any real symmetric matrix to be realizable as the admittance of a three-port resistive network containing six terminals and at most five positive elements, whose topological structure is properly restricted.
In this paper, we consider the nonlinear dynamical behaviors of some tabu leaning neuron models. We first consider a tabu learning single neuron model. By choosing the memory decay rate as a bifurcation parameter, we prove that Hopf bifurcation occurs in the neuron. The stability of the bifurcating periodic solutions and the direction of the Hopf bifurcation are determined by applying the normal form theory. We give a numerical example to verify the theoretical analysis. Then, we demonstrate the chaotic behavior in such a neuron with sinusoidal external input, via computer simulations. Finally, we study the chaotic behaviors in tabu learning two-neuron models, with linear and quadratic proximity functions respectively.
No abstract is provided for this article.
A new necessary and sufficient condition for the controllability of networked linear time-invariant systems is derived, where the network topology is general and the nodes have identical higher dimensional dynamics. The condition is easier to verify, explicitly illustrating how the network topology, node-system dynamics, external control inputs, and inner interactions altogether affect the controllability of the whole networked system. Furthermore, the controllability of the specified Cartesian product networks is revisited, revealing that the necessity of the controllability criterion established in the work presented by Chapman et al., does not hold. In view of this, a modified, necessary, and sufficient condition is established. The effectiveness of the conditions is demonstrated using several examples.
In this paper, impulsive control for master–slave synchronization schemes consisting of identical chaotic neural networks is studied. Impulsive control laws are derived based on linear static output feedback. A sufficient condition for global asymptotic synchronization of master–slave chaotic neural networks via output feedback impulsive control is established, in which synchronization is proven in terms of the synchronization errors between the full state vectors. An LMI-based approach for designing linear static output feedback impulsive control laws to globally asymptotically synchronize chaotic neural networks is discussed. With the help of LMI solvers, linear output feedback impulsive controllers can be easily obtained along with the bounds of the impulsive intervals for global asymptotic synchronization. The method is finally illustrated by numerical simulations.
We consider an Internet model with a single link accessed by a single source, which responds to congestion signals from the network, and study bifurcation of such a system. By choosing the gain parameter as a bifurcation parameter, we prove that Hopf bifurcation occurs. The stability of bifurcating periodic solutions and the direction of the Hopf bifurcation are determined by applying the normal form theory and the center manifold theorem. Finally, a numerical example is given to verify the theoretical analysis.
In this paper, a simple control method is proposed for stabilizing unstable equilibria of two typical classes of chaotic systems. For piecewise-linear chaotic systems, such as Chua's circuit, the control parameters can be selected via the pole placement technique from the linear control theory. For general nonlinear chaotic systems with continuously differentiable nonlinearities, particularly polynomial chaotic systems such as the Ro/spl uml/ssler system, Lorenz system, Chen's system, and the modified Chua's circuit with cubic nonlinearity, the control parameters can be chosen according to the pole placement technique and some additional theories of nonlinear ordinary differential equations. The criteria for the design of the control parameters are also investigated. This method is demonstrated to be highly robust against system parametric variations. To verify the effectiveness of the method, it is applied to both the original and the modified chaotic Chua's circuits, where satisfactory control performance is observed in simulations.
Complex networks are ubiquitous in the world. Many phenomena in nature can be described by the complex networks, such as brain structures, protein-protein interaction networks, scientific citation networks, food web, social interactions, the Internet, and so on. The study of complex networks is a young and active area of scientific research inspired largely by the empirical investigations of many real-world complex networks such as computer networks and social networks. It is very necessary to briefly review the main advances in the analysis, control and applications of complex networks over the last decade.
In the present paper, our aim is to determine both upper and lower bounds for all the Lyapunov exponents of a given finite-dimensional discrete map. To show the efficiency of the proposed estimation method, two examples are given, including the well-known Henon map and a coupled map lattice.
Evolutionary dynamics play a fundamental role in exploring the underlying mechanism of collective behaviors over a multi-agent network. Traditionally, evolutionary dynamics focus on the analysis of evolutionary behaviors of unstructured complex systems. However, recent research reveals that system structure is essential in the formation of collective behaviors. This article shows the intrinsic relation between structure and function of a complex dynamical network with evolutionary dynamics. In particular, the impact of node dynamics and network structure on evolutionary dynamics is investigated. Methods are given to find invasion hubs of a network and to design efficient networks for innovation diffusion. Moreover, it discusses some potential real-world applications and highlights some challenging problems for future studies.
In this note, it is shown that there exist two non-syndetically sensitive cascades defined on complete metric spaces whose product is cofinitely sensitive, answering negatively the Question 9.2 posed in Miller and Money (2017) [12]. Moreover, it is shown that there exists a syndetically sensitive semiflow ( G , X ) defined on a complete metric space X such that ( G 1 , X ) is not sensitive for some syndetic closed submonoid G 1 of G, answering negatively the Open question 3 posed in Money (2015) [13] and Question 43 posed in Miller (2017) [8].
No abstract is provided for this article.
