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OverviewFull Product DetailsAuthor: Luis GarridoPublisher: 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: 9783662137857ISBN 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 ContentsOn 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.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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