This work deals with the unsupervised Bayesian hidden Markov chain restoration extended to the non stationary case. Unsupervised restoration based on “ExpectationMaximization” (EM) or “Stochastic EM” (SEM) estimates considering the “Hidden Markov Chain” (HMC) model is quite efficient when the hidden chain is stationary. However, when the latter is not stationary, the unsupervised restoration re...

This paper reviews existing Non-Homogeneous Poisson Process (NHPP) software reliability models and their limitations, and proposes a more powerful non-homogeneous Markov model for the fault detection/removal problem. In addition, this non-homogeneous Markov model allows for the possibility of a nite time to repair a fault and for imperfections in the repair process. The proposed scheme provides...

This paper reviews existing Non-Homogeneous Poisson Process (NHPP) software reliability models and their limitations, and proposes a more powerful non-homogeneous Markov model for the fault detection/removal problem. In addition, this non-homogeneous Markov model allows for the possibility of a nite time to repair a fault and for imperfections in the repair process. The proposed scheme provides...