Knowledge-based neurocomputing /

Neurocomputing methods are loosely based on a model of the brain as a network of simple interconnected processing elements corresponding to neurons. These methods derive their power from the collective processing of artificial neurons, the chief advantage being that such systems can learn and adapt...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Cloete, Ian (Editor ), Zurada, Jacek M. (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cambridge, Mass. : MIT Press, ©2000.
Temas:
Neural computers.
Expert systems (Computer science)
Ordinateurs neuronaux.
Systèmes experts (Informatique)
COMPUTERS > Neural Networks.
Neural computers
COMPUTER SCIENCE/General
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Knowledge-based neurocomputing : past, present, and future
  • Architectures and techniques for knowledge-based neurocomputing
  • Symbolic knowledge representation in recurrent neural networks : insights from theoretical models of computation
  • Tutorial on neurocomputing of structures
  • Structural learning and rule discovery
  • VL₁ANN : transformation of rules to artificial neural networks
  • Integration of heterogeneous sources of partial domain knowledge
  • Approximation of differential equations using neural networks
  • Fynesse : a hybrid architecture for self-learning control
  • Data mining techniques for designing neural network time series predictors
  • Extraction of decision trees from artificial networks
  • Extraction of linguistic rules from data via neural networks and fuzzy approximation
  • Neural knowledge processing in expert systems.

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