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IROS
2008
IEEE
211views Robotics» more  IROS 2008»
14 years 3 months ago
GP-BayesFilters: Bayesian filtering using Gaussian process prediction and observation models
Abstract— Bayesian filtering is a general framework for recursively estimating the state of a dynamical system. The most common instantiations of Bayes filters are Kalman filt...
Jonathan Ko, Dieter Fox
RTSS
1998
IEEE
14 years 1 months ago
The Time-Triggered Model of Computation
: The Time-Triggered (TT) model of computation is a model for the representation and analysis of the design of large hard real-time systems. Central to this model is the concept of...
Hermann Kopetz
IJCAI
2003
13 years 10 months ago
Switching Hypothesized Measurements: A Dynamic Model with Applications to Occlusion Adaptive Joint Tracking
This paper proposes a dynamic model supporting multimodal state space probability distributions and presents the application of the model in dealing with visual occlusions when tr...
Yang Wang 0002, Tele Tan, Kia-Fock Loe
IJSYSC
2008
82views more  IJSYSC 2008»
13 years 9 months ago
Supply-chain modelling and control under proportional inventory-replenishment policies
A novel state-space model of a multi-node supply chain is presented, controlled via local proportional inventory-replenishment policies. The model is driven by a stochastic sequen...
C. I. Papanagnou, G. D. Halikias
ICASSP
2011
IEEE
13 years 28 days ago
Adaptive modelling with tunable RBF network using multi-innovation RLS algorithm assisted by swarm intelligence
— In this paper, we propose a new on-line learning algorithm for the non-linear system identification: the swarm intelligence aided multi-innovation recursive least squares (SIM...
Hao Chen, Yu Gong, Xia Hong