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Mutual information for stochastic differential equation with subfractional noises
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Junfeng Liu
Published/Copyright:
July 30, 2013
Abstract.
Motivated by the Gaussian channel models, we calculate the mutual information for processes described by multidimensional stochastic differential equations driven by sub-fractional Brownian motion.
Received: 2010-12-29
Revised: 2013-03-09
Accepted: 2013-03-15
Published Online: 2013-07-30
Published in Print: 2013-09-01
© 2013 by Walter de Gruyter Berlin Boston
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Articles in the same Issue
- Masthead
- An ergodic-type theorem for generalized Ornstein–Uhlenbeck processes
- A note on Feynman–Kac path integral representations for scalar wave motions
- Mutual information for stochastic differential equation with subfractional noises
- The quasi maximum likelihood approach to statistical inference on a nonstationary multivariate ARFIMA process
Keywords for this article
Subfractional Brownian motion;
mutual information;
Girsanov transform;
innovation process
Articles in the same Issue
- Masthead
- An ergodic-type theorem for generalized Ornstein–Uhlenbeck processes
- A note on Feynman–Kac path integral representations for scalar wave motions
- Mutual information for stochastic differential equation with subfractional noises
- The quasi maximum likelihood approach to statistical inference on a nonstationary multivariate ARFIMA process
