Entropy and information theory
Entropy and information theory
A novel interacting multiple model algorithm
Signal Processing
Robust mobile terminal tracking in NLOS environments using interacting multiple model algorithm
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Relative entropy rate based multiple hidden Markov model approximation
IEEE Transactions on Signal Processing
Sharper lower bounds for discrimination information in terms of variation (Corresp.)
IEEE Transactions on Information Theory
Practical stability of approximating discrete-time filters with respect to model mismatch
Automatica (Journal of IFAC)
| Hi-index | 0.08 |
Hybrid system representations have been exploited in a number of challenging modelling situations, including situations where the original nonlinear dynamics are too complex (or too imprecisely known) to be directly filtered. Unfortunately, the question of how to best design suitable hybrid system models has not yet been fully addressed, particularly in the situations involving model uncertainty. This paper proposes a novel joint state-measurement relative entropy rate based approach for design of hybrid system filters in the presence of (parameterised) model uncertainty. We also present a design approach suitable for suboptimal hybrid system filters. The benefits of our proposed approaches are illustrated through design examples and simulation studies.