Abstract. Given the substantial computational requirements of stochastic simulation, approximation is essential for efficient analysis of any realistic biochemical system. This pap...
We study stochastic models to mitigate the risk of poor Quality-of-Service (QoS) in computational markets. Consumers who purchase services expect both price and performance guaran...
Inthispaper we formulatethe Radon transform asa wnvolution integral over the Euclidean motion group (SE(2)) and provideaminimummeansquare error(MMSE) stochastic deconvolution meth...
A novel optimisation accelerator deploying neural network predictions and objective space direct manipulation strategies is presented. The concept of directing the search through ...
Stochastic performance models provide a powerful way of capturing and analysing the behaviour of complex concurrent systems. Traditionally, performance measures for these models ar...