Overview

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.

Full Product Details

Author:   Luis Garrido
Publisher:   Springer-Verlag Berlin and Heidelberg GmbH & Co. KG
Imprint:   Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Edition:   Softcover reprint of the original 1st ed. 1990
Volume:   368
Dimensions:   Width: 17.00cm , Height: 2.50cm , Length: 24.40cm
Weight:   0.830kg
ISBN:  

9783662137857

ISBN 10:   3662137852
Pages:   477
Publication Date:   23 August 2014
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand  
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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 basis of the locomotion of nematodes.- Reversibility in neural processing systems.- Lyapunov functional for neural networks with delayed interactions and statistical mechanics of temporal associations.- Semi-local signal processing in the visual system.- Statistical mechanics and error-correcting codes.- Synergetic computers — An alternative to neurocomputers.- Dynamics of the Kohonen map.- Equivalence between connectionist classifiers and logical classifiers.- On Potts-glass neural networks with biased patterns.- Ising-spin neural networks with spatial structure.- Kinetically disordered lattice systems.- A programming system for implementing neural nets.- An auto-augmenting neural network architecture for diagnostic reasoning.- Formal integrators and neural networks.- Disorderedmodels of acquired dyslexia.- Higher order memories in optimally structured neural networks.- Random Boolean networks for autoassociative memory: Optimization and sequential learning.

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