Biological and Artificial Computation: From Neuroscience to Technology
International Work-Conference on Artificial and Natural Neural Networks, IWANN¿97, Lanzarote, Canary Islands, Spain, June 4¿6, 1997 Proceedings Herausgegeben:Mira, Jose; Moreno-Diaz, Roberto; Cabestany, Joan
Biological and Artificial Computation: From Neuroscience to Technology
International Work-Conference on Artificial and Natural Neural Networks, IWANN¿97, Lanzarote, Canary Islands, Spain, June 4¿6, 1997 Proceedings Herausgegeben:Mira, Jose; Moreno-Diaz, Roberto; Cabestany, Joan
This book constitutes the refereed proceedings of the International Work-Conference on Artificial Neural Networks, IWANN'97, held in Lanzarote, Canary Islands, Spain, in June 1997. The volume presents 142 revised full papers selected from an overwhelming wealth of submissions. The volume is divided into sections on biological foundations of neural computation, formal tools and computational models of neurons and neural nets architectures, plasticity phenomena, complex systems dynamics, cognitive science and AI, neural nets simulation, emulation and implementation, methodology for data…mehr
This book constitutes the refereed proceedings of the International Work-Conference on Artificial Neural Networks, IWANN'97, held in Lanzarote, Canary Islands, Spain, in June 1997. The volume presents 142 revised full papers selected from an overwhelming wealth of submissions. The volume is divided into sections on biological foundations of neural computation, formal tools and computational models of neurons and neural nets architectures, plasticity phenomena, complex systems dynamics, cognitive science and AI, neural nets simulation, emulation and implementation, methodology for data analysis, task selection and net design, neural networks for perception, and neural networks for communications, control and robotics.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Microcircuits in the brain.- Some reflections on the relationships between neuroscience and computation.- Different types of temporal correlations obtained in pairs of thalamic visual neurons suggest different functional patterns of connectivity.- Development of on-off and off-on receptive fields using a semistochastic model.- The classification of spatial, chromatic, and intensity features of simple visual stimuli by a network of retinal ganglion cells.- Geometric model of orientation tuning dynamics in striate neurons.- Neuronal circuitry in the medial cerebral cortex of lizards.- Interactions between environmental and hormonal oscillations induce plastic changes in a simple neuroendocrine transducer.- Current Source Density analysis as a tool to constrain the parameter space in hippocampal CA1 neuron models.- Spontaneous activity of hippocampal cells in various physiological states.- Neural network model of striatal complex.- Symmetry and self-organization of the oculomotor neural integrator.- Quantal neural mechanisms underlying movement execution and motor learning.- A model of cerebellar saccadic motor learning using qualitative reasoning.- Balance between intercellular coupling and input resistance as a necessary requirement for oscillatory electrical activity in pancreatic ?-cells.- Mechanisms of synchronization in the hippocampus and its role along development.- Analysis of synfire chains above saturation.- Allometry in the Justo Gonzalo's model of the sensorial cortex.- Systems models of retinal cells: A classical example.- A generic formulation of neural nets as a model of parallel and self-programming computation.- Using an artificial neural network for studying the interneuronal layer of a leech neuronal circuit.- Capacity and parasitic fixed points control in a recursive neural network.- The use of prior knowledge in neural network configuration and training.- A model for heterogeneous neurons and its use in configuring neural networks for classification problems.- A computation theory for orientation-selective simple cells based on the MAP estimation principle and Markov random fields.- Competition between feed-forward and lateral information processing in layered neural networks.- Computing functions with spiking neurons in temporal coding.- An introduction to Fuzzy State Automata.- Statistical analysis of regularization constant From Bayes, MDL and NIC points of view.- Building digital libraries from paper documents, using ART based neuro-fuzzy systems.- Parallelization of connectionist models based on a symbolic formalism.- Generic neural network model and simulation toolkit.- A neural-fuzzy technique for interpolating spatial data via the use of learning curve.- Task decomposition based on class relations: A modular neural network architecture for pattern classification.- Lower bounds of computational power of a synaptic calculus.- Feed Forward Neural Network entities.- Astrocytes and slow learning in the formation of distal cortical associations.- Adaptation and other dynamic effects on neural signal transfer.- Hebbian learning in networks of spiking neurons using temporal coding.- An associative learning model for coupled neural oscillators.- Random perturbations to Hebbian synapses of associative memory using a genetic algorithm.- Phase memory in oscillatory networks.- Strategies for autonomous adaptation and learning in dynamical networks.- Modeling the parallel development of multiple featuremaps and topography in visual cortex.- Stability and hebbian learning in populations of probabilistic neurons.- Stochastic approximation techniques and circuits and systems associated tools for neural network optimization.- Recursive hetero-associative memories for translation.- Universal Binary and Multi-Valued Neurons paradigm: Conception, learning, applications.- Learning a Markov process with a synchronous Boltzmann machine.- The ?-EM algorithm: A block connectable generalized leaning tool for neural networks.-
Microcircuits in the brain.- Some reflections on the relationships between neuroscience and computation.- Different types of temporal correlations obtained in pairs of thalamic visual neurons suggest different functional patterns of connectivity.- Development of on-off and off-on receptive fields using a semistochastic model.- The classification of spatial, chromatic, and intensity features of simple visual stimuli by a network of retinal ganglion cells.- Geometric model of orientation tuning dynamics in striate neurons.- Neuronal circuitry in the medial cerebral cortex of lizards.- Interactions between environmental and hormonal oscillations induce plastic changes in a simple neuroendocrine transducer.- Current Source Density analysis as a tool to constrain the parameter space in hippocampal CA1 neuron models.- Spontaneous activity of hippocampal cells in various physiological states.- Neural network model of striatal complex.- Symmetry and self-organization of the oculomotor neural integrator.- Quantal neural mechanisms underlying movement execution and motor learning.- A model of cerebellar saccadic motor learning using qualitative reasoning.- Balance between intercellular coupling and input resistance as a necessary requirement for oscillatory electrical activity in pancreatic ?-cells.- Mechanisms of synchronization in the hippocampus and its role along development.- Analysis of synfire chains above saturation.- Allometry in the Justo Gonzalo's model of the sensorial cortex.- Systems models of retinal cells: A classical example.- A generic formulation of neural nets as a model of parallel and self-programming computation.- Using an artificial neural network for studying the interneuronal layer of a leech neuronal circuit.- Capacity and parasitic fixed points control in a recursive neural network.- The use of prior knowledge in neural network configuration and training.- A model for heterogeneous neurons and its use in configuring neural networks for classification problems.- A computation theory for orientation-selective simple cells based on the MAP estimation principle and Markov random fields.- Competition between feed-forward and lateral information processing in layered neural networks.- Computing functions with spiking neurons in temporal coding.- An introduction to Fuzzy State Automata.- Statistical analysis of regularization constant From Bayes, MDL and NIC points of view.- Building digital libraries from paper documents, using ART based neuro-fuzzy systems.- Parallelization of connectionist models based on a symbolic formalism.- Generic neural network model and simulation toolkit.- A neural-fuzzy technique for interpolating spatial data via the use of learning curve.- Task decomposition based on class relations: A modular neural network architecture for pattern classification.- Lower bounds of computational power of a synaptic calculus.- Feed Forward Neural Network entities.- Astrocytes and slow learning in the formation of distal cortical associations.- Adaptation and other dynamic effects on neural signal transfer.- Hebbian learning in networks of spiking neurons using temporal coding.- An associative learning model for coupled neural oscillators.- Random perturbations to Hebbian synapses of associative memory using a genetic algorithm.- Phase memory in oscillatory networks.- Strategies for autonomous adaptation and learning in dynamical networks.- Modeling the parallel development of multiple featuremaps and topography in visual cortex.- Stability and hebbian learning in populations of probabilistic neurons.- Stochastic approximation techniques and circuits and systems associated tools for neural network optimization.- Recursive hetero-associative memories for translation.- Universal Binary and Multi-Valued Neurons paradigm: Conception, learning, applications.- Learning a Markov process with a synchronous Boltzmann machine.- The ?-EM algorithm: A block connectable generalized leaning tool for neural networks.-
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