This paper explores the potential of acausal modelling tools for a simple, but challenging process engineering benchmark problem. Matlab/Simulink illustrates a traditional block d...
Two of the most commonly used models in computational learning theory are the distribution-free model in which examples are chosen from a fixed but arbitrary distribution, and the ...
Following current modeling paradigms, most processes are captured in the form of modeling a desired intent, often using success probabilities. In addition, only special roles that...
The general aim of this talk is to advocate a combinatorial perspective, together with its methods, in the investigation and study of models of computation structures. This, of cou...
—This paper presents an auxiliary model based stochastic gradient parameter estimation algorithm for multiinput output-error systems by minimizing a quadratic cost function. The ...