Abstract: The stability problem for a class of stochastic neural networks with Markovian jump parameters and leakage delay is addressed in this study. The sufficient condition to ensure an exponentially stable stochastic neural networks system is presented and proven with Lyapunov functional theory, stochastic stability technique and linear matrix inequality method. The effect of leakage delay ...

This paper considers the stability of moments of stochastic systems, such as stability of the mean or mean-square stability. The exponential growth behavior of moments is compared to almost sure exponential growth via Lyapunov exponents. We develop a series of indices that are useful to describe system performance under random perturbations. The theory is applied to two examples, including an e...

In this paper, the global asymptotic stability of delayed cellular neural networks of neutral-type is investigated. A novel delay-dependent criterion for the stability using the Lyapunov stability theory and linear matrix inequality (LMI) framework is presented. Since the condition is dependent on the size of time delay, it is usually less conservative than delay-independent ones. Two numerical...

Mathematical control theory provides the theoretical foundations that undergird many modern technologies, including aeronautics, biotechnology, communications networks, manufacturing, and models of climate change. During the past fifteen years, there have been numerous exciting developments at the interface of control engineering and mathematical control theory. Many of these advances were base...

Motivated by their important role in smooth dynamical systems, Lyapunov exponents have been conceived decades ago as a means to study the stability of cellular automata (CAs). More precisely, they quantify their sensitive dependence on initial conditions. As a next step towards the establishment of a dynamical systems theory of CAs that is inspired by its analogue for smooth dynamical systems, ...

We study a class of discrete-time bidirectional ring neural network model with delay. We discuss the asymptotic stability of the origin and the existence of Neimark-Sacker bifurcations, by analyzing the corresponding characteristic equation. Employing M-matrix theory and the Lyapunov functional method, global asymptotic stability of the origin is derived. Applying the normal form theory and the...

this paper proposes a hybrid control scheme for the synchronization of two chaotic duffing oscillator system, subject to uncertainties and external disturbances. the novelty of this scheme is that the linear quadratic regulation (lqr) control, sliding mode (sm) control and gaussian radial basis function neural network (grbfnn) control are combined to chaos synchronization with respect to extern...

In this paper we introduce a new modeling paradigm for shortest path games representation with Petri nets. Whereas previous works have restricted attention to tracking the net using Bellman’s equation as a utility function, this work uses a Lyapunov-like function. In this sense, we change the traditional cost function by a trajectory-tracking function which is also an optimal cost-to-target fun...

This paper proposes new criteria for stability and performance of nonlinear interconnected systems by smoothly generalizing a recently-developed method of the state-dependent scaling. The criteria are directly related to Lyapunov functions so that they show how to construct Lyapunov functions which establish desired stability and performance explicitly. A set of popular Lyapunov stability crite...

This paper proposes a novel approach based on Lyapunov function method to analyse the stability of photovoltaic (PV) systems. The Lyapunov function is formulated using the method of quadratic forms, i.e., Krasovskii’s method. The stability of the photovoltaic systems under different operating conditions is analysed based on the formulated Lyapunov function. A comparison of stability analysis us...