Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.1/2288
Título: Speeding up a learning algorithm for multilayer perceptrons using the MAPS Environment
Autor: Daniel, H. A.
Ruano, A. E.
Palavras-chave: Multiprogramming
Neural Networks
Parallel Algorithms
Multiprocessing Systems
Digital Signal Processors
Data: 2004
Citação: Daniel, H.; Ruano, A. E. Speeding up a Learning Algorithm for Multilayer Perceptrons using the MAPS Environment, Trabalho apresentado em 6th Portuguese Conference on Automatic Control (Controlo 2004), In 6th Portuguese Conference on Automatic Control (Controlo 2004), Faro, 2004.
Resumo: Artificial neural networks, as non-linear adaptive elements, have been proposed for applications in adaptive control. Their ability to accurately approximate large classes of non-linear functions made them also a valuable tool for non-linear systems identification. However, in some cases, the parameter estimation phase may take considerable amount of time, and this is crucial in real-time applications. One way of speeding up these learning algorithms consists in executing them over a multiprocessor system. In this paper an implementation over MAPS integrated development environment, which automatically generates a parallel application from a sequential description of a learning algorithm for multilayer perceptrons is presented.
Peer review: yes
URI: http://hdl.handle.net/10400.1/2288
Aparece nas colecções:FCT2-Artigos (em revistas ou actas indexadas)

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