This paper investigates the problem of noise-to-state practical stability in mean (NSpS-M) (which is a natural generalization of noise-to-state stability in mean) and the problem of almost sure global asymptotic stability (GAS a.s.) for a class of random nonlinear time-varying impulsive switched systems. By using the notions of average impulsive switched interval and Poisson process, unified sufficient stability criteria on NSpS-M and GAS a.s. are derived. Two remarkable distinctions from the existing results lie in that: (1) stabilizing, inactive and destabilizing impulses are simultaneously considered; (2) the coefficient of the derivative of a Lyapunov function is allowed to be a time-varying function which can be both positive and negative and may even be unbounded. As an accompaniment, a less conservative unified criterion on NSpS-M for a special case is also presented by taking into account the stabilization role of the gain constant of the time-varying coefficient. Two examples are provided to illustrate the effectiveness of our derived criteria.

This paper addresses the stability problem for a class of switched nonlinear systems subject to random disturbances whose τ-order moments (τ > 1) are finite. First, some general conditions are given to guarantee the existence and uniqueness of solutions to random switched systems. Next, these results are used to deduce the criteria of noise-to-state stability under probabilistic switching signal. Then, the average dwell-time approach is adopted to study the noise-to-state stability, the e ^λt -weighted (integral) noise-to-state stability and the global asymptotic stability of random switched systems. All the criteria on global existence and stability of solutions are developed by virtue of multiple Lyapunov functions. Finally, two numerical examples are given to demonstrate the validity of the theoretical results.

This paper establishes the stability criteria for genetic regulatory networks with random disturbances. We assume the nonlinear feedback regulation function to satisfy the sector-like condition and the random perturbation to have a finite second-order moment. First, under the globally Lipschitz condition, the existence and uniqueness of solution to random genetic regulatory networks are considered by exploiting an iterative approximation method. Then, by feat of the random analysis method and matrix technique, sufficient conditions are given to guarantee the noise-to-state stability in mean and globally asymptotic stability in probability, respectively. At last, two simulation examples are exploited in order to verify the validity of the proposed theory.