Neural Networks : A comprehensive Foundation / Simon Haykin
Tipo de material:
TextoIdioma: en Detalles de publicación: New Jersey : Prentice Hall, 1994Descripción: xvi, 696 p.: il.;, 25 cmTema(s): AUTOORGANIZACION | INTELIGENCIA ARTIFICIAL | NEURAL NETWARKS | REDES NEURONALES
| Tipo de ítem | Biblioteca de origen | Signatura | Estado | Fecha de vencimiento | Código de barras | Reserva de ítems |
|---|---|---|---|---|---|---|
LIBRO
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Biblioteca de la Facultad de Ingeniería UNMDP | 519.7 519.7 H 28 (Navegar estantería(Abre debajo)) | Disponible | 8861 |
Apéndices p. 617
Incluye abreviaciones y símbolos
Problemas al finald de cada capítulo
What is a neural network?. Learning process. Correlation matrix memory. The perceptron. Least-Mean-Square algorithm. Multilayer perceptrons. Back-propagation and differentiation. Radial-Basis Function networks. Recurrent networks rooted in statistical physics. Self-Organizing systems I: Hebbian learning. Self-organizing systems II: Competitive learning. Self-organizing systems III: Information-theoretic models. Modular networks. Temporal processing. Neurodynamics. VLSI Iplementations of neural networks. Pseudoinverse matrix memory. A general tool for convergence. Analysis of stochastic. Approximation algorithms. Statical thermodynamics. Fokker-plank equation.