In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...
Neural decoding is an important task for understanding how the biological nervous system performs computation and communication. This paper introduces a novel continuous neural de...
We propose a novel strategy for training neural networks using sequential Monte Carlo algorithms. This global optimisation strategy allows us to learn the probability distribution...
We report new results on the corner classification approach to training feedforward neural networks. It is shown that a prescriptive learning procedure where the weights are simp...
In this paper, we present a neural networks and image analysis based approach to assessing colour deviations in an offset printing process from direct measurements on halftone mult...