Non-fragile Finite-time Stabilization for Discrete Mean-field Stochastic Systems

In this paper, the problem of non-fragile finite-time stabilization for linear discrete mean-field stochastic systems is studied. The uncertain characteristics in control parameters are assumed to be random satisfying the Bernoulli distribution. A new approach called the ``state transition matrix method" is introduced and some necessary and sufficient conditions are derived to solve the underlying stabilization problem. The Lyapunov theorem based on the state transition matrix also makes a contribution to the discrete finite-time control theory. One practical example is provided to validate the effectiveness of the newly proposed control strategy

Study on H

This paper studies the H- index problem. We obtain a necessary and sufficient condition of H- index larger than γ>0. A generalized differential equation is introduced and it is proved that its solvability and the feasibility of the H- index are equivalent. We extend the deterministic cases to the stochastic models. Our results can be used to fault detection filter analysis. Finally, the effectiveness of the proposed results is illustrated by an example

A New Model for Capturing the Spread of Computer Viruses on Complex-Networks

Based on complex network, this paper proposes a novel computer virus propagation model which is motivated by the traditional SEIRQ model. A systematic analysis of this new model shows that the virus-free equilibrium is globally asymptotically stable when its basic reproduction is less than one, and the viral equilibrium is globally attractive when the basic reproduction is greater than one. Some numerical simulations are finally given to illustrate the main results, implying that these results are applicable to depict the dynamics of virus propagation

Enhancing cross layer monitoring on open optical transport networks

Continuous monitoring of key network elements is instrumental in intelligent control and predictive analysis. This demonstration illustrates implementation challenges that are encountered in cross-layer monitoring of optical transport networks in an open-source network operations platform

Feedback Stabilization for a Class of Nonlinear Stochastic Systems with State- and Control-Dependent Noise

This paper mainly studies the state feedback stabilizability of a class of nonlinear stochastic systems with state- and control-dependent noise. Some sufficient conditions on local and global state feedback stabilizations are given in linear matrix inequalities (LMIs) and generalized algebraic Riccati equations (GAREs). Some obtained results improve the previous work