P. S. Neelakanta, Dolores Degroff

Neural Network Modeling

Statistical Mechanics and Cybernetic Perspectives

• Gebundenes Buch

Produktbeschreibung

This text offers a cohesive approach to the statistical mechanics and principles of cybemetics as a basis for neural network modelling. The book highlights the theoretical perspectives and explanatory projections of the visualisation of neuronal interactions, most of which represent the most current and controversial concepts in the field.

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Neural Network Modeling offers a cohesive approach to the statistical mechanics and principles of cybernetics as a basis for neural network modeling. It brings together neurobiologists and the engineers who design intelligent automata to understand the physics of collective behavior pertinent to neural elements and the self-control aspects of neurocybernetics. The theoretical perspectives and explanatory projections portray the most current information in the field, some of which counters certain conventional concepts in the visualization of neuronal interactions.

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Produktdetails

• Verlag: CRC Press
• Seitenzahl: 262
• Erscheinungstermin: 12. Juli 1994
• Englisch
• Abmessung: 240mm x 161mm x 19mm
• Gewicht: 561g
• ISBN-13: 9780849324888
• ISBN-10: 0849324882
• Artikelnr.: 22461690

Autorenporträt

Neelakanta, P. S.; DeGroff, Dolores

Inhaltsangabe

Introduction. Neural and Brain Complex. Concepts of Mathematical
Neurobiology. Pseudo-Thermodynamics of Neural Activity. The Physics of
Neural Activity: A Statistical Mechanics Perspective. Stochastic Dynamics
of the Neural Complex. Neural Field Theory: Quasiparticle Dynamics and Wave
Mechanics Analogies of Neural Networks. Informatic Aspects of
Neurocybernetics. Appendices: Magnetism and the Ising Spin-Glass Model.
Matrix Methods in Little's Model. Overlap of Replicas and Replica Symmetry.
Bibliography. Index.