Linear Models with Hidden Markov Sources via Replica Method
Accepted version
Peer-reviewed
Repository URI
Repository DOI
Change log
Authors
Truong, LV
Abstract
We estimate the minimum mean square error (MMSE) of the linear model under hidden Markov priors. Our estimates are based on the replica method in statistical physics. We show that under the MMSE estimator, the linear model with hidden Markov sources is decoupled into single-input AWGN channels with state information available at both encoder and decoder where the state distribution follows the left Perron-Frobenius eigenvector with unit Manhattan norm of the stochastic matrix of Markov chains.
Description
Keywords
49 Mathematical Sciences, 46 Information and Computing Sciences, 40 Engineering, 4905 Statistics
Journal Title
IEEE International Symposium on Information Theory - Proceedings
Conference Name
2021 IEEE International Symposium on Information Theory (ISIT)
Journal ISSN
2157-8095
Volume Title
2021-July
Publisher
IEEE