Statistical Mechanics of Neural Networks : Proceedings of the XIth Sitges Conference Sitges, Barcelona, Spain, 3–7 June 1990. 1st ed. 1990

種類:

電子ブック

責任表示:

edited by Luis Garrido

出版情報:

Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 1990

著者名:

• Garrido, Luis.
• SpringerLink (Online service)

シリーズ名:

Lecture Notes in Physics ; 368

ISBN:

9783540468080 [3540468080]    

注記:

On the statistical-mechanical formulation of neural networks -- Model neurons: From Hodgkin-Huxley to hopfield -- Statistical mechanics for networks of analog neurons -- Properties of neural networks with multi-state neurons -- Adaptive recurrent neural networks and dynamic stability -- Neuronal oscillators: Experiments and models -- Neuronal networks in the hippocampus involved in memory -- Basins of attraction and spurious states in neural networks -- Tailoring the performance of attractor neural networks -- Learning and optimization -- Statistical dynamics of learning -- Learning and retrieving marked patterns -- Learning algorithm for binary synapses -- Statistical mechanics of the perceptron with maximal stability -- Simulation and hardware implementation of competitive learning neural networks -- Learning in multilayer networks: A geometric computational approach -- Storage capacity of diluted neural networks -- Dynamics and storage capacity of neural networks with sign-constrained weights -- The neural
Combined for researchers and graduate students the articles from the Sitges Summer School together form an excellent survey of the applications of neural-network theory to statistical mechanics and computer-science biophysics. Various mathematical models are presented together with their interpretation, especially those to do with collective behaviour, learning and storage capacity, and dynamical stability.

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