Training recurrent neural networks is hard. Recently it has however been discovered that it is possible to just construct a random recurrent topology, and only train a single linea...
Benjamin Schrauwen, David Verstraeten, Jan M. Van ...
This paper presents a neural network approach with successful implementation for the robot task-sequencing problem. The problem addresses the sequencing of tasks comprising loadin...
We propose a new VLSI layout methodology which addresses the main problems faced in Deep Sub-Micron (DSM) integrated circuit design. Our layout "fabric" scheme eliminate...
Sunil P. Khatri, Amit Mehrotra, Robert K. Brayton,...
Abstract. In this paper, neural networks trained with the back-propagation algorithm are applied to predict the future values of time series that consist of the weekly demand on it...
This paper describes an evaluation of a neural network technique for modelling fuel spray penetration in the cylinder of a diesel internal combustion engine. The model was implemen...
Simon D. Walters, Shaun H. Lee, Cyril Crua, Robert...