An Introduction to the Modeling of Neural Networks
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BeschreibungThis text is a beginning graduate-level introduction to neural networks, focusing on current theoretical models, examining what these models can reveal about how the brain functions, and discussing the ramifications for psychology, artificial intelligence and the construction of a new generation of intelligent computers.
InhaltsverzeichnisPreface; Acknowledgments; 1. Introduction; 2. The biology of neural networks: a few features for the sake of non-biologists; 3. The dynamics of neural networks: a stochastic approach; 4. Hebbian models of associative memory; 5. Temporal sequences of patterns; 6. The problem of learning in neural networks; 7. Learning dynamics in 'visible' neural networks; 8. Solving the problem of credit assignment; 9. Self-organization; 10. Neurocomputation; 11. Neurocomputers; 12. A critical view of the modeling of neural networks; References; Index.
Pressestimmen"...a beginning graduate-level text that discusses a wide range of neural network models and algorithms: simulated annealing, Aleksander's model, Boltzmann machine, perceptron, backpropagation, Hopfield's models, self-organization, and others. It may be especially useful for those with no or limited knowledge of the biology of neural networks and their relation to artificial neural networks." George Georgiou, Mathematical Reviews "...excellent introductions to this exciting new enterprise...this comprehensive summary of research results in neural networks with both practical and biological applications provides an invaluable resource for the graduate student or researcher working in this field...summarizes some of the important questions that remain in our understanding of biological neural networks that may be addressed with greater integration of neural network modeling and biological experimentation." Roderick V. Jensen, American Journal of Physics
Untertitel: 'Collection Alea-Saclay'. New. Sprache: Englisch.
Verlag: CAMBRIDGE UNIV PR
Erscheinungsdatum: November 1992
Seitenanzahl: 492 Seiten