Redes Neuronales Artificiales. Un Enfoque Práctico : P. Isasi Viñuela, I. M. Galván. Pearson Educación, 2004. ISBN 84-205-4025-0
Artificial Neural Networks belong to the sub-symbolic branch of Artificial Intelligence since they allow to find the solution of a problem without the need of knowing the algorithm necessary to solve it. This turns them into a tool based on an approach completely different from that used by conventi...
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| Formato: | Articulo Revision |
| Lenguaje: | Inglés |
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2004
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/9491 http://journal.info.unlp.edu.ar/wp-content/uploads/JCST-Aug04-BR1.pdf |
| Aporte de: |
| Sumario: | Artificial Neural Networks belong to the sub-symbolic branch of Artificial Intelligence since they allow to find the solution of a problem without the need of knowing the algorithm necessary to solve it. This turns them into a tool based on an approach completely different from that used by conventional Computing.
Artificial neural networks (ANN) have been inspired in how the brain works and in the way its cells relate to each other. Technological advances provide ever-greater resources to represent really complex structures, perform computations at high speed and in parallel. This has indeed motivated research on this kind of tool. |
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