In this paper, we consider stochastic optimal control of Markov Jump Linear Systems with state feedback but without observation of the jumping parameter. The proposed control law is assumed to be linear with constant gains that can be obtained from the necessary optimality conditions using an iterative algorithm. The proposed approach is demonstrated in a numerical example.

This paper presents closed-form expressions to exactly match three moments and a correlation parameter into a Markovian arrival process of second order (MAP(2)), whose marginal distribution is a mixture of two exponentials. Mixtures of exponential distributions are popular in distribution fitting. In the two-dimensional setting, we study to which extent correlations can be introduced in a seque...

Independent cascade (IC) model is a widely used influence propagation for social networks. In this paper, we incorporate the concept and techniques from causal inference to study identifiability of parameters observational data in extended IC with unobserved confounding factors, which models more realistic scenarios but rarely studied modeling before. We provide conditions or unidentifiability ...

In this paper, we propose an unsupervised color image classification algorithm based on a Markov random field (MRF) model. In the MRF model, we use the CIE-luv color metric because it is close to human perception when computing color differences. On the other hand, intensity and chroma information is separated in this space. Without parameter estimation, our model would not be useful in real-li...

In this paper, we show how Markovian strategies used to solve well-known segmentation problems such as motion estimation, motion detection, motion segmentation, stereovision, and color segmentation can be significantly accelerated when implemented on programmable graphics hardware. More precisely, we expose how the parallel abilities of a standard graphics processing unit usually devoted to ima...

An unsupervised color image segmentation algorithm is presented, using a Markov random ®eld (MRF) pixel classi®cation model. We propose a new method to estimate initial mean vectors e€ectively even if the histogram does not have clearly distinguishable peaks. The only parameter supplied by the user is the number of classes. Ó 2001 Elsevier Science B.V. All rights reserved.

Full counting statistics of electron transport is a powerful diagnostic tool for probing the nature of quantum transport beyond what is obtainable from the average current or conductance measurement alone. In particular, the non-Markovian dynamics of quantum dot molecule plays an important role in the nonequilibrium electron tunneling processes. It is thus necessary to understand the non-Markov...

Markovian arrival processes are a powerful class of stochastic processes to represent stochastic workloads that include autocorrelation in performance or dependability modeling. However, fitting the parameters of a Markovian arrival process to given measurement data is non-trivial and most known methods focus on a single class case, where all events are of the same type and only the sequence of...

This article examines mixed ℋ -infinity and passivity synchronization of Markovian jumping neutral-type complex dynamical network (MJNTCDN) models with randomly occurring coupling delays actuator faults. The are considered to design the networks in practice. These complied certain Bernoulli distribut...