We propose a Markov process model for spike-frequency adapting neural ensembles which synthesizes existing mean-adaptation approaches, population density methods, and inhomogeneou...
Eilif Mueller, Lars Buesing, Johannes Schemmel, Ka...
This paper presents an approximation method for numerically solving general Markov modulated fluid models which are widely used in modelling communications and computer systems. ...
Abstract. In this paper we consider two performance modelling techniques from the perspectives of model construction, generation of an underlying continuous time Markov process, an...
The compact Genetic Algorithm (cGA) is an Estimation of Distribution Algorithm that generates offspring population according to the estimated probabilistic model of the parent pop...