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A Modified Arnoldi Iteration for Transition Probability Matrices of Reversible Markov Chains.
|Title:||A Modified Arnoldi Iteration for Transition Probability Matrices of Reversible Markov Chains.|
|Authors:||Chong, Joseph M. U.|
|Contributors:||Electrical Engineering (department)|
|Date Issued:||Aug 2018|
|Publisher:||University of Hawaiʻi at Mānoa|
|Abstract:||Reversible Markov chains are used for modeling many physical and network phenomena.|
The second largest eigenvalue magnitude of the transition probability matrix
gives a upper bound on the mixing time of a reversible Markov chain, but is incalculable
for large transition probability matrices using typical eigenvalue algorithms. We
present the Modified Arnoldi iteration - a modification of the Arnoldi iteration for
reversible Markov chains that utilizes sample estimates where matrix operations may
be infeasible, thereby being a possible option when usual algorithms are nonviable.
|Description:||M.S. Thesis. University of Hawaiʻi at Mānoa 2018.|
|Rights:||All UHM dissertations and theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission from the copyright owner.|
|Appears in Collections:||
M.S. - Electrical Engineering|
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