TY - GEN

T1 - A recursive learning algorithm for model reduction of Hidden Markov Models

AU - Deng, Kun

AU - Mehta, Prashant G.

AU - Meyn, Sean P.

AU - Vidyasagar, Mathukumalli

PY - 2011/12/1

Y1 - 2011/12/1

N2 - This paper is concerned with a recursive learning algorithm for model reduction of Hidden Markov Models (HMMs) with finite state space and finite observation space. The state space is aggregated/partitioned to reduce the complexity of the HMM. The optimal aggregation is obtained by minimizing the Kullback-Leibler divergence rate between the laws of the observation process. The optimal aggregated HMM is given as a function of the partition function of the state space. The optimal partition is obtained by using a recursive stochastic approximation learning algorithm, which can be implemented through a single sample path of the HMM. Convergence of the algorithm is established using ergodicity of the filtering process and standard stochastic approximation arguments.

AB - This paper is concerned with a recursive learning algorithm for model reduction of Hidden Markov Models (HMMs) with finite state space and finite observation space. The state space is aggregated/partitioned to reduce the complexity of the HMM. The optimal aggregation is obtained by minimizing the Kullback-Leibler divergence rate between the laws of the observation process. The optimal aggregated HMM is given as a function of the partition function of the state space. The optimal partition is obtained by using a recursive stochastic approximation learning algorithm, which can be implemented through a single sample path of the HMM. Convergence of the algorithm is established using ergodicity of the filtering process and standard stochastic approximation arguments.

UR - http://www.scopus.com/inward/record.url?scp=84860650368&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84860650368&partnerID=8YFLogxK

U2 - 10.1109/CDC.2011.6160826

DO - 10.1109/CDC.2011.6160826

M3 - Conference contribution

AN - SCOPUS:84860650368

SN - 9781612848006

T3 - Proceedings of the IEEE Conference on Decision and Control

SP - 4674

EP - 4679

BT - 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011

T2 - 2011 50th IEEE Conference on Decision and Control and European Control Conference, CDC-ECC 2011

Y2 - 12 December 2011 through 15 December 2011

ER -