A generalized Markov chain representation of fault dynamics is presented for the case that available modeling of fault growth physics and future environmental stresses can be represented by two independent stochastic process models. A contrived but representatively challenging example will be presented and analyzed, in which uncertainty in the modeling of fault growth physics is represented by ...

Continuous-time nonlinear stochastic differential state and measurement equations, all of which have coefficients capable of abrupt changes at a random time, are considered; finite-state jump Markov chains are used to model the changes. Conditional probability densities, which are essential in obtaining filtered estimates for these hybrid systems, are then derived. They are governed by a couple...

The computational operations of stochastic computing (SC) are governed by probability rules which is different from conventional arithmetic computations. Applications of SC to digital signal and image processing problems have been recently reported in the literature. To improve the computational performance of SC based finite impulse response (FIR) digital filters, a new stochastic inner produc...

This paper is concerned with the finite-horizon H∞ fault estimation problem for a class of nonlinear stochastic time-varying systems with both randomly occurring faults and fading channels. The system model (dynamical plant) is subject to Lipschitz-like nonlinearities and the faults occur in a random way governed by a set of Bernoulli distributed white sequences. The system measurements are tra...

This paper considers the problem of the simultaneous finite-time event-triggered control and fault detection for a class of continuous-time singular Markovian jump mixed delay systems (SMJDSs) under asynchronous switching. In order to develop the control and detection objectives, the mode-dependent fault detection filters and dynamic feedback event-triggered-based controllers are designed and t...

the purpose of this study is to compare the results of different probabilistic methods such as the perturbation method, stochastic finite element method (sfem) and monte carlo method. these methods were used to study the convergence of direct approach for slope stability analysis and are developed for a linear soil behavior. in this study, two dimensional random fields are used and both the fir...

we focus on the use of two stable and accurate explicit finite difference schemes in order to approximate the solution of stochastic partial differential equations of it¨o type, in particular, parabolic equations. the main properties of these deterministic difference methods, i.e., convergence, consistency, and stability, are separately developed for the stochastic cases.

in this paper, a high-order and conditionally stable stochastic difference scheme is proposed for the numerical solution of $rm ithat{o}$ stochastic advection diffusion equation with one dimensional white noise process. we applied a finite difference approximation of fourth-order for discretizing space spatial derivative of this equation. the main properties of deterministic difference schemes,...