We study how the dependence of a simulation output on an uncertain parameter can be determined, when simulations are computationally expensive and so can only be run for very few p...
Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in ...
The focus of this paper is the problem of recursive estimation for uncertain multisensor linear discrete-time systems. We herein propose a new suboptimal filtering algorithm. The b...
This paper presents a new supervisory control scheme, which is based on a control-relevant switching logic. Unlike most of the existing switching methods considering only estimato...
B-tree and index into two layers of abstraction. In addition, this paper provides algorithms for (i) concurrency control and recovery including locking of individual keys and of co...