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...
In this paper, we propose a new approach of solving the stereopsis problem with a discrete-time cellular neural network(DTCNN) where each node has connectionsonly with its local n...
Abstract. As the disparity between processor and memory speed continues to widen, the exploitation of locality of reference in shared-memory multiprocessors becomes an increasingly...
This paper presents two novel features of an emergent data visualization method coined "cellular ants": unsupervised data class labeling and shape negotiation. This metho...
Andrew Vande Moere, Justin James Clayden, Andy Don...
This paper presents an environment based on SystemC for architecture specification of programmable systems. Making use of the new architecture description language ArchC, able to ...
Pablo Viana, Edna Barros, Sandro Rigo, Rodolfo Aze...