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140122 ||| eng |
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|a 9783540468080
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1 |
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|a Garrido, Luis
|e [editor]
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| 245 |
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|a Statistical Mechanics of Neural Networks
|h Elektronische Ressource
|b Proceedings of the XIth Sitges Conference Sitges, Barcelona, Spain, 3–7 June 1990
|c edited by Luis Garrido
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| 250 |
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|a 1st ed. 1990
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| 260 |
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|a Berlin, Heidelberg
|b Springer Berlin Heidelberg
|c 1990, 1990
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| 300 |
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|a VI, 477 p
|b online resource
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|a 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 --
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|a 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 --
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|a Random Boolean networks for autoassociative memory: Optimization and sequential learning
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| 653 |
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|a Complex Systems
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| 653 |
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|a Thermodynamics
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a System theory
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Mathematical physics
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| 653 |
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|a Theoretical, Mathematical and Computational Physics
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|a eng
|2 ISO 639-2
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| 989 |
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|b SBA
|a Springer Book Archives -2004
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|a Lecture Notes in Physics
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| 028 |
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|a 10.1007/3-540-53267-6
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| 856 |
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|u https://doi.org/10.1007/3-540-53267-6?nosfx=y
|x Verlag
|3 Volltext
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|a 536.7
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| 520 |
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|a 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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