We analyze a distributed algorithm for estimation of scalar parameters belonging to nodes in a mobile network from noisy relative measurements. The motivation comes from the problem of clock skew and offset estimation for the purpose of time synchronization. The time variation of the network was modeled as a Markov chain. The estimates are shown to be mean square convergent under fairly weak as...

We propose a distributed algorithm for estimation of clock skew and offset of the nodes of a mobile network. The problem is cast as an estimation from noisy relative measurements. The time variation of the network was modeled as a Markov chain. The estimates are shown to be mean square convergent under fairly weak assumptions on the Markov chain, as long as the union of the graphs is connected....

This paper surveys and relates the basic concepts of process algebra and the modelling of continuous time Markov chains. It provides basic introductions to both fields, where we also study the Markov chains from an algebraic perspective, viz. that of Markov chain algebra. We then proceed to study the interrelation of reactive processes and Markov chains in this setting, and introduce the algebr...

This paper introduces a new multinomial approach unifying the computation of confidence intervals for Markovian models. Starting from a method used for homogeneous Markov chains, we show that it can be applied on models incorporating a hidden component. We consider three models derived from the basic homogeneous Markov chain: the Mixture Transition Distribution (MTD) model, the Hidden Markov Mo...

-Markovsemantic indexing algorithm based on the controlled Markov chain modeling framework. Controlled Markov chain models are used to describe the temporal evolution of low-level visual descriptors extracted from the semantic indexing model. Propose a semantic indexing algorithm which uses both text and image retrieval system.The entire user Queries selected by randomly. An image retrieval sys...

Abstract A novel Markovian network evolution model is introduced and analysed by means of information theory. It will be proved that the model, called chain, a stationary ergodic stochastic process. Therefore, asymptotic equipartition property can applied to it. The model’s entropy rate typical sequences are also explored. Extracting particular from methods simulate in continuous time domain di...

This paper proposes markovian models in portfolio theory and risk management. At first, we describe discrete time optimal allocation models. Then, we examine the investor’s optimal choices either when the returns are uniquely determined by their mean and variance or when they are modeled by a Markov chain. We subject these models to back-testing on out-of-sample data, in order to assess their f...

Many large-scale stochastic systems, such as telecommunications networks, can be modelled using a continuous-time Markov chain. However, it is frequently the case that a satisfactory analysis of their time dependent, or even equilibrium behaviour, is impossible. In this paper we propose a new method of analyzing Markovian models, whereby the existing transition structure is replaced by a more a...

File access patterns for application startup are fixed and predictable. More precisely, they would obey the Markovian property of each future access depending only on the current access. In this project, we attempt to learn the Markov chain transition probabilities, where each file access is a state in the chain. But since multiple applications may run at the same time, the file access chains f...