Ergodicity of Fuzzy Markov Chains Based on Simulation Using Halton Sequences


Authors

Behrouz Fathi Vajargah - Department of Statistics, University of Guilan, Rasht, Iran Maryam Gharehdaghi - Department of Statistics, University of Guilan, Rasht, Iran


Abstract

We first introduce fuzzy finite Markov chains and present some of their fundamental properties based on possibility theory. We also bring in a way to convert fuzzy Markov chains to classic Markov chains. In addition, we simulate fuzzy Markov chain using different sizes. It is observed that the most of fuzzy Markov chains not only do have an ergodic behavior, but also they are periodic. Finally, using Halton quasi-random sequence we generate some fuzzy Markov chains which compared to the ones generated by the RAND function of MATLAB. Therefore, we improve the periodicity behavior of fuzzy Markov chains.


Share and Cite

  • Share on Facebook
  • Share on Twitter
  • Share on LinkedIn
ISRP Style

Behrouz Fathi Vajargah, Maryam Gharehdaghi, Ergodicity of Fuzzy Markov Chains Based on Simulation Using Halton Sequences, Journal of Mathematics and Computer Science, 4 (2012), no. 3, 380--385

AMA Style

Fathi Vajargah Behrouz, Gharehdaghi Maryam, Ergodicity of Fuzzy Markov Chains Based on Simulation Using Halton Sequences. J Math Comput SCI-JM. (2012); 4(3):380--385

Chicago/Turabian Style

Fathi Vajargah, Behrouz, Gharehdaghi, Maryam. "Ergodicity of Fuzzy Markov Chains Based on Simulation Using Halton Sequences." Journal of Mathematics and Computer Science, 4, no. 3 (2012): 380--385


Keywords


MSC


References