A New Optimization Model for the Construction of Markov Chains
We study the problem of construction of the transition probability matrix of a Markov chain from a given steady-state probability distribution. We note that for this inverse problem, there are many possible transition probability matrices sharing the same steady-state probability distribution. Therefore extra constraint has to be introduced so as to narrow down the set of solutions or even a unique solution. We propose to consider maximizing the generalized entropy rate of the Markov chain with a penalty cost as the extra criterion. We first give a mathematical formulation of the inverse problem as a maximization problem. We then apply the Lagrange multiplier method to the original problem. Numerical examples in contrast with are given to demonstrate the effectiveness of the proposed method.
Markov Chains Inverse Problem
Wai-Ki Ching Yang Cong
AMAC Laboratory Department of Mathematics The University of Hong Kong Pokfulam Road, Hong Kong
国际会议
三亚
英文
551-555
2009-04-24（万方平台首次上网日期，不代表论文的发表时间）