In this paper, we study the optimal way of distributing sensors in a random field to minimize the estimation distortion. We show that this problem is equivalent to certain proble...
Most of the work which attempts to give bounds on the generalization error of the hypothesis generated by a learning algorithm is based on methods from the theory of uniform conve...
— In this paper, a new method to design an observer for nonlinear systems described by Takagi-Sugeno (TS) model, with unmeasurable premise variables, is proposed. Most of existin...
This paper contains two important contributions for the development of possibilistic causal networks. The first one concerns the representation of interventions in possibilistic ...
Abstract. We define a probabilistic contract framework for the construction of component-based embedded systems, based on the theory of Interactive Markov Chains. A contract specif...