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...
Abstract— This paper presents scheduling strategies for sensing workload in wireless sensor networks using Divisible Load Theory (DLT), which offers a tractable model and realist...
We give machine characterisations and logical descriptions of a number of parameterized complexity classes. The focus of our attention is the class W[P], which we characterise as ...
Abstract. Most previous theoretical study of the complexity of the constraint satisfaction problem has considered a simplified version of the problem in which all variables have t...
—We develop a simple stochastic fluid model that seeks to expose the fundamental characteristics and limitations of P2P streaming systems. This model accounts for many of the es...