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Technical Program

Paper Detail

Paper IDD1-S6-T3.3
Paper Title Linear Models with Hidden Markov Sources via Replica Method
Authors Lan V. Truong, The University of Cambridge, United Kingdom
Session D1-S6-T3: Inference in Graphical Models
Chaired Session: Monday, 12 July, 23:40 - 00:00
Engagement Session: Tuesday, 13 July, 00:00 - 00:20
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.