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...
There is a growing need to analyze and optimize the stand-by component of power in digital circuits designed for portable and battery-powered applications. Since these circuits re...
David Blaauw, Steven M. Martin, Trevor N. Mudge, K...
Dynamic memory storage has been widely used for years in computer science. However, its use in real-time systems has not been considered as an important issue, and memory manageme...
A model-constrained adaptive sampling methodology is proposed for reduction of large-scale systems with high-dimensional parametric input spaces. Our model reduction method uses a ...
— The efforts to construct a national scale Grid computing environment have brought unprecedented computing capacity and complicacy. Exploiting this complex infrastructure requir...