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.
Related Books
Boundary Element Methods for Heat Transfer with Phase Change Problems: Theory and Application
On Generalized Growth rates of Integer Translated Entire and Meromorphic Functions
Introductory Statistics
Advanced Mathematical Applications in Data Science
Advanced Calculus - Fundamentals of Mathematics
Advanced Numerical Methods for Complex Environmental Models: Needs and Availability
Advances in Time Series Forecasting
Advances in Time Series Forecasting
Current Developments in Mathematical Sciences
Current Developments in Mathematical Sciences