Linear optimal prediction and innovations representations of hidden Markov models

[摘要] The topic of this paper is linear optimal prediction of hidden Markov models (HMMs) and innovations representations of HMMs. Our interest in these topics primarily arise from subspace estimation methods, which are intrinsically linked to such representations. For HMMs, derivation of innovations representations is complicated by non-minimality of the corresponding state space representations, and requires the solution of algebraic Riccati equations under non-minimality assumptions. (C) 2003 Elsevier B.V. All rights reserved.

[发布日期] 2003-11-01

[关键词] hidden Markov model;innovations representation;Kalman filter;non-minimality;prediction error representation;Riccati equation