Artificial neural networks (ANN) have been widely used for both classification and prediction. This paper is focused on the prediction problem in which an unknown function is appr...
Minimization methods for training feed-forward networks with Backpropagation are compared. Feedforward network training is a special case of functional minimization, where no expli...
Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C...
When learning a mixture model, we suffer from the local optima and model structure determination problems. In this paper, we present a method for simultaneously solving these prob...
Abstract. This paper proposes a novel algorithm for complete exact patternmatching focusing the specificities of protein sequences (alphabet of 20 symbols) but, also highly efficie...
One of the major challenges in the field of neurally driven evolved autonomous agents is deciphering the neural mechanisms underlying their behavior. Aiming at this goal, we have d...
Alon Keinan, Ben Sandbank, Claus C. Hilgetag, Isaa...