Ebook: Neural Network Dynamics: Proceedings of the Workshop on Complex Dynamics in Neural Networks, June 17–21 1991 at IIASS, Vietri, Italy

Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.

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Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.

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Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.
Content:
Front Matter....Pages i-xii
Front Matter....Pages 1-1
Information and pattern capacities in neural associative memories with feedback for sparse memory patterns....Pages 3-18
Associative Reinforcement Training Using Probabilistic RAM Nets....Pages 19-29
Unlearning and Its Relevance to REM Sleep: Decorrelating Correlated Data....Pages 30-43
Optimal Architectures and High-Order Networks....Pages 44-56
Deterministic Networks with Ternary Neurons....Pages 57-74
Nets, Structure, Hierarchy....Pages 75-89
Training Random Asymmetric ‘Neural’ Networks Towards Chaos — A Progress Report....Pages 90-102
Complex dynamics of a discrete time model of a neuron....Pages 103-121
Front Matter....Pages 123-123
Correlated Neuronal Firing: a Clue to the Integrative Functions of Cortex?....Pages 125-139
Two-Layered Physiology-Oriented Neuronal Network Models that Combine Dynamic Feature Linking via Synchronization with a Classical Associative Memory....Pages 140-154
Theoretical framework for analysing the behaviour of real and simulated neural networks....Pages 155-169
Coupled Neuronal Oscillatory Systems....Pages 170-179
Gamma-Band Oscillations in a Cortical Model....Pages 180-190
Information Processing by Dynamical Interaction of Oscillatory Modes in Coupled Cortical Networks....Pages 191-207
Analysis of Oscillatory Regimes of a Coupled Neural Oscillator System with Application to Visual Cortex Modeling....Pages 208-225
Systems of Relaxation Oscillators with Time-Delayed Coupling....Pages 226-233
Cortical Coherent Activity Induced by Thalamic Oscillations....Pages 234-249
A ‘microscopic’ model of collective oscillations in the cortex....Pages 250-257
Temporal Processing in Brain Activity....Pages 258-290
Front Matter....Pages 291-291
Structural Properties of Proteins Predicted by Neural Networks....Pages 293-304
Front Matter....Pages 291-291
Nuclear Phenomenology with Neural Nets....Pages 305-322
Applying Neural Networks to Resonance Search in High Energy Physics....Pages 323-329
Visual Comparison of Information Storage in Various Neural Network Models....Pages 330-338
Front Matter....Pages 339-339
Activation Dynamics of Space-Variant Continuous Networks....Pages 341-355
Hierarchical Neural Representations by Synchronized Activity: a Concept for Visual Pattern Recognition....Pages 356-370
Back Matter....Pages 371-371

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Neural Network Dynamics is the latest volume in the Perspectives in Neural Computing series. It contains papers presented at the 1991 Workshop on Complex Dynamics in Neural Networks, held at IIASS in Vietri, Italy. The workshop encompassed a wide range of topics in which neural networks play a fundamental role, and aimed to bridge the gap between neural computation and computational neuroscience. The papers - which have been updated where necessary to include new results - are divided into four sections, covering the foundations of neural network dynamics, oscillatory neural networks, as well as scientific and biological applications of neural networks. Among the topics discussed are: A general analysis of neural network activity; Descriptions of various network architectures and nodes; Correlated neuronal firing; A theoretical framework for analyzing the behaviour of real and simulated neuronal networks; The structural properties of proteins; Nuclear phenomenology; Resonance searches in high energy physics; The investigation of information storage; Visual cortical architecture; Visual processing. Neural Network Dynamics is the first volume to cover neural networks and computational neuroscience in such detail. Although it is primarily aimed at researchers and postgraduate students in the above disciplines, it will also be of interest to researchers in electrical engineering, medicine, psychology and philosophy.
Content:
Front Matter....Pages i-xii
Front Matter....Pages 1-1
Information and pattern capacities in neural associative memories with feedback for sparse memory patterns....Pages 3-18
Associative Reinforcement Training Using Probabilistic RAM Nets....Pages 19-29
Unlearning and Its Relevance to REM Sleep: Decorrelating Correlated Data....Pages 30-43
Optimal Architectures and High-Order Networks....Pages 44-56
Deterministic Networks with Ternary Neurons....Pages 57-74
Nets, Structure, Hierarchy....Pages 75-89
Training Random Asymmetric ‘Neural’ Networks Towards Chaos — A Progress Report....Pages 90-102
Complex dynamics of a discrete time model of a neuron....Pages 103-121
Front Matter....Pages 123-123
Correlated Neuronal Firing: a Clue to the Integrative Functions of Cortex?....Pages 125-139
Two-Layered Physiology-Oriented Neuronal Network Models that Combine Dynamic Feature Linking via Synchronization with a Classical Associative Memory....Pages 140-154
Theoretical framework for analysing the behaviour of real and simulated neural networks....Pages 155-169
Coupled Neuronal Oscillatory Systems....Pages 170-179
Gamma-Band Oscillations in a Cortical Model....Pages 180-190
Information Processing by Dynamical Interaction of Oscillatory Modes in Coupled Cortical Networks....Pages 191-207
Analysis of Oscillatory Regimes of a Coupled Neural Oscillator System with Application to Visual Cortex Modeling....Pages 208-225
Systems of Relaxation Oscillators with Time-Delayed Coupling....Pages 226-233
Cortical Coherent Activity Induced by Thalamic Oscillations....Pages 234-249
A ‘microscopic’ model of collective oscillations in the cortex....Pages 250-257
Temporal Processing in Brain Activity....Pages 258-290
Front Matter....Pages 291-291
Structural Properties of Proteins Predicted by Neural Networks....Pages 293-304
Front Matter....Pages 291-291
Nuclear Phenomenology with Neural Nets....Pages 305-322
Applying Neural Networks to Resonance Search in High Energy Physics....Pages 323-329
Visual Comparison of Information Storage in Various Neural Network Models....Pages 330-338
Front Matter....Pages 339-339
Activation Dynamics of Space-Variant Continuous Networks....Pages 341-355
Hierarchical Neural Representations by Synchronized Activity: a Concept for Visual Pattern Recognition....Pages 356-370
Back Matter....Pages 371-371
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