Markov Chain Process (Theory and Cases)

Computational Science Issues

Author(s): Carlos Polanco * .

Pp: 87-92 (6)

DOI: 10.2174/9789815080476123010015

* (Excluding Mailing and Handling)

Abstract

This chapter introduces a Hierarchical Markov Chain Process over a hierarchical network whose nodes are Discrete-Time Markov Chain and Continuous-Time Markov Chain Processes. We consider it useful to carry out this non-exhaustive analysis to discuss the advantages and disadvantages of a random walk of this nature and its possible application, particularly in real-time and in unsupervised mode. Examples are provided under the discrete and continuous schemes. 

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