Title :
Entropy rate of continuous-state hidden Markov chains
Author :
Han, Guangyue ; Marcus, Brian
Author_Institution :
Univ. of Hong Kong, Hong Kong, China
Abstract :
We prove that under mild positivity assumptions, the entropy rate of a continuous-state hidden Markov chain, observed when passing a finite-state Markov chain through a discrete-time continuous-output channel, is analytic as a function of the transition probabilities of the underlying Markov chain. We further prove that the entropy rate of a continuous-state hidden Markov chain, observed when passing a mixing finite-type constrained Markov chain through a discrete-time Gaussian channel, is smooth as a function of the transition probabilities of the underlying Markov chain.
Keywords :
Gaussian channels; entropy; hidden Markov models; probability; continuous-state hidden Markov chains; discrete-time Gaussian channel; discrete-time continuous-output channel; entropy rate; finite-state Markov chain; finite-type constrained Markov chain; mild positivity assumptions; probability; Constraint theory; Entropy; Gaussian channels; Hidden Markov models; Integral equations; Magnetic recording; Probability density function; Tin;
Conference_Titel :
Information Theory Proceedings (ISIT), 2010 IEEE International Symposium on
Conference_Location :
Austin, TX
Print_ISBN :
978-1-4244-7890-3
Electronic_ISBN :
978-1-4244-7891-0
DOI :
10.1109/ISIT.2010.5513590