Steepest Descent. Discrete Iterative Optimization. Markov Chain Monte Carlo (MCMC). NOTE: NOT FOR DISTRIBUTION!!

We consider the stability properties and stabilizing problem of sampled-data networked controlled linear systems with Markovian packet losses. A binary Markov chain is used to characterize the packet loss phenomenon of the network. Then with the Markovian packet loss assumption, we obtain a discrete-time augmented Markov jump linear system which describes the continuous-time linear system evolv...

In Hidden Markov Models (HMM) the probability distribution of response Yt (∀t = 1, 2, . . . , T ) at each observation time is conditionally specified on the current hidden or latent state Xt. The sequence of hidden states follows a first order time-homogeneous Markov chain. Discrete time or continuous time HMM are respectively specified by T ⊆ N or T ⊆ R (from now on DHMM and CHMM). In this wor...

In this paper, we develop some matrix Poisson’s equations satisfied by the mean and variance of the mixing time in an irreducible positive-recurrent discrete-time Markov chain with infinitely-many levels, and provide a computational framework for the solution to the matrix Poisson’s equations by means of the UL-type of RGfactorization as well as the generalized inverses. In an important special...

this paper is devoted to the study of determining optimal process mean in system production with the two markets for the sale of goods. in this paper, we developed an absorbing markov chain model in production systems where all items are inspected %100 for conformance with their specification limits. when the value of the quality characteristic of an item falls below a lower limit, the item is ...