Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International Work-Conference on Artificial and Natural Neural N by Jose MiraConnectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International Work-Conference on Artificial and Natural Neural N by Jose Mira

Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International…

EditorJose Mira

Paperback | June 5, 2001

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Underlying most of the IWANN calls for papers is the aim to reassume some of the motivations of the groundwork stages of biocybernetics and the later bionics formulations and to try to reconsider the present value of two basic questions. The?rstoneis:"Whatdoesneurosciencebringintocomputation(thenew bionics)?" That is to say, how can we seek inspiration in biology? Titles such as "computational intelligence", "arti?cial neural nets", "genetic algorithms", "evolutionary hardware", "evolutive architectures", "embryonics", "sensory n- romorphic systems", and "emotional robotics" are representatives of the present interest in "biological electronics" (bionics). Thesecondquestionis:"Whatcanreturncomputationtoneuroscience(the new neurocybernetics)?" That is to say, how can mathematics, electronics, c- puter science, and arti?cial intelligence help the neurobiologists to improve their experimental data modeling and to move a step forward towards the understa- ing of the nervous system? Relevant here are the general philosophy of the IWANN conferences, the sustained interdisciplinary approach, and the global strategy, again and again to bring together physiologists and computer experts to consider the common and pertinent questions and the shared methods to answer these questions.
Title:Connectionist Models of Neurons, Learning Processes, and Artificial Intelligence: 6th International…Format:PaperbackDimensions:868 pages, 9.17 × 6.1 × 0.07 inPublished:June 5, 2001Publisher:Springer Berlin HeidelbergLanguage:English

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ISBN - 10:3540422358

ISBN - 13:9783540422358

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Table of Contents

Foundations of Connectionism and Biophysical Models of Neurons.- Dendrites: The Last-Generation Computers.- Homogeneity in the Electrical Activity Pattern as a Function of Intercellular Coupling in Cell Networks.- A Realistic Computational Model of the Local Circuitry of the Cuneate Nucleus.- Algorithmic Extraction of Morphological Statistics from Electronic Archives of Neuroanatomy.- What Can We Compute with Lateral Inhibition Circuits?.- Neuronal Models with Current Inputs.- Decoding the Population Responses of Retinal Ganglions Cells Using Information Theory.- Numerical Study of Effects of Co-transmission by Substance P and Acetylcholine on Synaptic Plasticity in Myenteric Neurons.- Neurobiological Modeling of Bursting Response During Visual Attention.- Sensitivity of Simulated Striate Neurons to Cross-Like Stimuli Based on Disinhibitory Mechanism.- Synchronisation Mechanisms in Neuronal Networks.- Detection of Oriented Repetitive Alternating Patterns in color Images.- Synchronization in Brain - Assessment by Electroencephalographic Signals.- Strategies for the Optimization of Large Scale Networks of Integrate and Fire Neurons.- Structural and Functional Models of Neurons.- A Neural Network Model of Working Memory (Processing of "What" and "Where" Information).- Orientation Selectivity of Intracortical Inhibitory Cells in the Striate Visual Cortex: A Computational Theory and a Neural Circuitry.- Interpreting Neural Networks in the Frame of the Logic of Lukasiewicz.- Time-Dispersive Effects in the J. Gonzalo's Research on Cerebral Dynamics.- Verifying Properties of Neural Networks.- Algorithms and Implementation Architectures for Hebbian Neural Networks.- The Hierarchical Neuro-Fuzzy BSP Model: An Application in Electric Load Forecasting.- The Chemical Metaphor in Neural Computation.- The General Neural-Network Paradigm for Visual Cryptography.- ?-DTB, Discrete Time Backpropagation with Product Units.- Neocognitron-Type Network for Recognizing Rotated and Shifted Patterns with Reduction of Resources.- Classification with Synaptic Radial Basis Units.- A Randomized Hypercolumn Model and Gesture Recognition.- Heterogeneous Kohonen Networks.- Divided-Data Analysis in a Financial Case Classification with Multi-dendritic Neural Networks.- Neuro Fuzzy Systems: State-of-the-Art Modeling Techniques.- Generating Linear Regression Rules from Neural Networks Using Local Least Squares Approximation.- Speech Recognition Using Fuzzy Second-Order Recurrent Neural Networks.- A Measure of Noise Immunity for Functional Networks.- A Functional-Neural Network for Post-Nonlinear Independent Component Analysis.- Optimal Modular Feedfroward Neural Nets Based on Functional Network Architectures.- Optimal Transformations in Multiple Linear Regression Using Functional Networks.- Learning and Other Plasticity Phenomena, and Complex Systems Dynamics.- Generalization Error and Training Error at Singularities of Multilayer Perceptrons.- Bistable Gradient Neural Networks: Their Computational Properties.- Inductive Bias in Recurrent Neural Networks.- Accelerating the Convergence of EM-Based Training Algorithms for RBF Networks.- Expansive and Competitive Neural Networks.- Fast Function Approximation with Hierarchical Neural Networks and Their Application to a Reinforcement Learning Agent.- Two Dimensional Evaluation Reinforcement Learning.- Comparing the Learning Processes of Cognitive Distance Learning and Search Based Agent.- Selective Learning for Multilayer Feedforward Neural Networks.- Connectionist Models of Cortico-Basal Ganglia Adaptive Neural Networks During Learning of Motor Sequential Procedures.- Practical Consideration on Generalization Property of Natural Gradient Learning.- Novel Training Algorithm Based on Quadratic Optimisation Using Neural Networks.- Non-symmetric Support Vector Machines.- Natural Gradient Learning in NLDA Networks.- AUTOWISARD: Unsupervised Modes for the WISARD.- Neural Steering: Difficult and Impossible Sequential Problems for Gradient Descent.- Analysis of Scaling Exponents of Waken and Sleeping Stage in EEG.- Model Based Predictive Control Using Genetic Algorithms. Application to Greenhouses Climate Control.- Nonlinear Parametric Model Identification with Genetic Algorithms. Application to a Thermal Process.- A Comparison of Several Evolutionary Heuristics for the Frequency Assignment Problem.- GA Techniques Applied to Contour Search in Images of Bovine Livestock.- Richer Network Dynamics of Intrinsically Non-regular Neurons Measured through Mutual Information.- RBF Neural Networks, Multiobjective Optimization and Time Series Forecasting.- Evolving RBF Neural Networks.- Evolutionary Cellular Configurations for Designing Feed-Forward Neural Networks Architectures.- A Recurrent Multivalued Neural Network for the N-Queens Problem.- A Novel Approach to Self-Adaptation of Neuro-Fuzzy Controllers in Real Time.- Expert Mutation Operators for the Evolution of Radial Basis Function Neural Networks.- Studying Neural Networks of Bifurcating Recursive Processing Elements - Quantitative Methods for Architecture Design.- Topology-Preserving Elastic Nets.- Optimization with Linear Constraints in the Neural Network.- Optimizing RBF Networks with Cooperative/Competitive Evolution of Units and Fuzzy Rules.- Study of Chaos in a Simple Discrete Recurrence Neural Network.- Genetic Algorithm versus Scatter Search and Solving Hard MAX-W-SAT Problems.- A New Approach to Evolutionary Computation: Segregative Genetic Algorithms (SEGA).- Evolution of Firms in Complex Worlds: Generalized NK Model.- Learning Adaptive Parameters with Restricted Genetic Optimization Method.- Solving NP-Complete Problems with Networks of Evolutionary Processors.- Using SOM for Neural Network Visualization.- Comparison of Supervised Self-Organizing Maps Using Euclidian or Mahalanobis Distance in Classification Context.- Introducing Multi-objective Optimization in Cooperative Coevolution of Neural Networks.- STAR - Sparsity through Automated Rejection.- Ordinal Regression with K-SVCR Machines.- Large Margin Nearest Neighbor Classifiers.- Reduced Support Vector Selection by Linear Programs.- Edge Detection in Noisy Images Using the Support Vector Machines.- Initialization in Genetic Algorithms for Constraint Satisfaction Problems.- Evolving High-Posterior Self-Organizing Maps.- Using Statistical Techniques to Predict GA Performance.- Multilevel Genetic Algorithm for the Complete Development of ANN.- Graph Based GP Applied to Dynamical Systems Modeling.- Nonlinear System Dynamics in the Normalisation Process of a Self-Organising Neural Network for Combinatorial Optimisation.- Continuous Function Optimisation via Gradient Descent on a Neural Network Approxmiation Function.- An Evolutionary Algorithm for the Design of Hybrid Fiber Optic-Coaxial Cable Networks in Small Urban Areas.- Channel Assignment for Mobile Communications Using Stochastic Chaotic Simulated Annealing.- Artificial Intelligence and Cognitive Processes.- Seeing is Believing: Depictive Neuromodelling of Visual Awareness.- DIAGEN-WebDB: A Connectionist Approach to Medical Knowledge Representation and Inference.- Conceptual Spaces as Voltage Maps.- Determining Hyper-planes to Generate Symbolic Rules.- Automatic Symbolic Modelling of Co-evolutionarily Learned Robot Skills.- ANNs and the Neural Basis for General Intelligence.- Knowledge and Intelligence.- Conjecturing the Cognitive Plausibility of an ANN Theorem-Prover.