2018/06/25 by Vladislav B. Tadić, Arnaud Doucet, Tadic, Vladislav Z. B. +1
Computer Science · Engineering · Mathematics · #Control Systems and Identification #FOS: Computer and information sciences #FOS: Mathematics #Information Theory (cs.IT) #Markov Chains and Monte Carlo Methods #Statistics Theory (math.ST) #Target Tracking and Data Fusion in Sensor Networks
paper · doi:10.48550/arxiv.1806.09589
openalex publication_date 2018/06/25 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The analyticity of the entropy and relative entropy rates of continuous-state hidden Markov models is studied here. Using the analytic continuation principle and the stability properties of the optimal filter, the analyticity of these rates is shown for analytically parameterized models. The obtained results hold under relatively mild conditions and cover several classes of hidden Markov models met in practice. These results are relevant for several (theoretically and practically) important problems arising in statistical inference, system identification and information theory.