Statistical Mechanics of Neural Networks

Table of Contents

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   Book Overview
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   Chapter 36 Introduction On the statistical-mechanical formulation of neural networks
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   Chapter 37 Model neurons: From Hodgkin-Huxley to hopfield
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   Chapter 38 Statistical mechanics for networks of analog neurons
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   Chapter 39 Properties of neural networks with multi-state neurons
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   Chapter 40 Adaptive recurrent neural networks and dynamic stability
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   Chapter 41 Neuronal oscillators: Experiments and models
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   Chapter 42 Neuronal networks in the hippocampus involved in memory
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   Chapter 43 Basins of attraction and spurious states in neural networks
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    Chapter 44 Tailoring the performance of attractor neural networks
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    Chapter 45 Learning and optimization
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    Chapter 46 Statistical dynamics of learning
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    Chapter 47 Learning and retrieving marked patterns
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    Chapter 48 Learning algorithm for binary synapses
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    Chapter 49 Statistical mechanics of the perceptron with maximal stability
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    Chapter 50 Simulation and hardware implementation of competitive learning neural networks
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    Chapter 51 Learning in multilayer networks: A geometric computational approach
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    Chapter 52 Storage capacity of diluted neural networks
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    Chapter 53 Dynamics and storage capacity of neural networks with sign-constrained weights
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    Chapter 54 The neural basis of the locomotion of nematodes
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    Chapter 55 Reversibility in neural processing systems
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    Chapter 56 Lyapunov functional for neural networks with delayed interactions and statistical mechanics of temporal associations
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    Chapter 57 Semi-local signal processing in the visual system
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    Chapter 58 Statistical mechanics and error-correcting codes
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    Chapter 59 Synergetic computers — An alternative to neurocomputers
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    Chapter 60 Dynamics of the Kohonen map
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    Chapter 61 Equivalence between connectionist classifiers and logical classifiers
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    Chapter 62 On Potts-glass neural networks with biased patterns
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    Chapter 63 Ising-spin neural networks with spatial structure
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    Chapter 64 Kinetically disordered lattice systems
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    Chapter 65 A programming system for implementing neural nets
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    Chapter 66 An auto-augmenting neural network architecture for diagnostic reasoning
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    Chapter 67 Formal integrators and neural networks
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    Chapter 68 Disordered models of acquired dyslexia
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    Chapter 69 Higher order memories in optimally structured neural networks
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    Chapter 70 Random Boolean networks for autoassociative memory: Optimization and sequential learning