Computational methods in neural modeling
著者
書誌事項
Computational methods in neural modeling
（Lecture notes in computer science, 2686 . 7th International Work-Conference on Artificial and Natural Neural Networks,
Springer, c2003
大学図書館所蔵 件 / 全25件
-
V.2686007.6/L507/v.268605956655,
V.2687007.6/L507/v.268705956664, 007.6/L507/v.268605956655 -
該当する所蔵館はありません
- すべての絞り込み条件を解除する
注記
Includes bibliographies and index
内容説明・目次
内容説明
The global purpose of IWANN conferences has been to provide a broad and - terdisciplinary forum for the interplay between neuroscience and computation. Our dream has been, and still is: (1) ?nd ways to understand the physiol- ical, symbolic and cognitive nature of the nervous system (NS) with the help of computational and engineering tools; and (2) ?nd rich and insightful sources of inspiration in biology, to develop new materials, mechanisms and probl- solving methods (PSM) of value in engineering and computation. As all of us knowwell, this dreamstarted with the AncientGreeks, reappearedin the fo- dational stage of neurocybernetics and bionics, and is now broadly accepted in the scienti?c community under di?erent labels such as computational neu- science(CN) andarti?cialneuralnets (ANN), orgenetic algorithmsandhybrid neuro-fuzzy systems. We have also to recognize that there is a considerable lack of credibility associated with CN and ANN among some researchers, both from biology and from the engineering and computation area.
Potential causes of this scepticism could be the lack of methodology, formal tools, and real-world applications, in the engineering area, and the lack also of formal tools for cognitive process modeling. There is also the possibility of the computational paradigm being inappropriate to explain cognition, because of the "representational" character ofanycomputationalmodel. Some"moresituated"approachesarelookingback to the "neurophysiological epistemology" of the 1960's (mind in a body) to searchdirectlyforthemechanismsthatcouldembodythecognitiveprocess,and this means some fresh air for our old dream of connectionism.
目次
Biological Models.- Modeling Neuronal Firing in the Presence of Refractoriness.- A Study of the Action Potential Initiation Site Along the Axosomatodendritic Axis of Neurons Using Compartmental Models.- Real Neurons and Neural Computation: A Summary of Thoughts.- Synchronous firing in a population of inhibitory interneurons coupled by electrical and chemical synapses.- Stochastic Networks with Subthreshold Oscillations and Spiking Activity.- Selective Inactivation of Neuronal Dendritic Domains: Computational Approach to Steady Potential Gradients.- Intermittent burst synchronization in neural networks.- Diffusion Associative Network: Diffusive Hybrid Neuromodulation and Volume Learning.- The Minimum-Variance Theory Revisited.- Sleep and wakefulness in the cuneate nucleus: a computational study.- Effiects of different connectivity patterns in a model of cortical circuits.- A Digital Neural Model of Visual Deficits in Parkinson's Disease.- Intersensorial Summation as a Nonlinear Contribution to Cerebral Excitation.- Interacting Modalities through Functional Brain Modeling.- Life-long learning: consolidation of novel events into dynamic memory representations.- Functional Models.- Real-time Sound Source Localization and Separation based on Active Audio-Visual Integration.- Hierarchical Neuro-Fuzzy Systems.- A functional spiking neuron hardware oriented model.- SO(2)-Networks as Neural Oscillators.- A Rotated Kernel Probabilistic Neural Network (RKPNN) for Multi-class Classification.- Independent Residual Analysis for Temporally Correlated Signals.- MLP+H: a Hybrid Neural Architecture Formed by the Interaction of Hopfield and Multi-Layer Perceptron Neural Networks.- Linear unit relevance in multiclass NLDA networks.- Bootstrap for model selection: linear approximation of the optimism.- Learning.- A learning rule to model the development of orientation selectivity in visual cortex.- Sequence learning using the neural coding.- Improved Kernel Learning Using Smoothing Parameter Based Linear Kernel.- Automatic Car Parking: A Reinforcement Learning Approach.- Discriminative Training of the Scanning N-Tuple Classifier.- A Wrapper Approach with Support Vector Machines for Text Categorization.- Robust Expectation Maximization Learning Algorithm for Mixture of Experts.- Choosing among algorithms to improve accuracy.- Evolutionary Approach to Overcome Initialization Parameters in Classification Problems.- Text Categorisation Using a Partial-Matching Strategy.- A new learning method for single layer neural networks based on a regularized cost function.- A better selection of patterns in lazy learning radial basis neural networks.- An Iterative Fuzzy Prototype Induction Algorithm.- A Recurrent Multivalued Neural Network for codebook generation in Vector Quantization.- The recurrent IML-network.- Estimation of Multidimensional Regression Model with Multilayer Perceptrons.- Principal Components Analysis Competitive Learning.- Self-Organizing Systems.- Progressive Concept Formation in Self-organising Maps.- Supervised Classification with Associative SOM.- Neural Implementation of Dijkstra's Algorithm..- Spurious minima and basins of attraction in higher-order Hopfield networks.- Cooperative Co-evolution of Multilayer Perceptrons.- A statistical model of pollution-caused pulmonary crises.- A new penalty-based criterion for model selection in regularized nonlinear models.- Data Driven Multiple Neural Network Models Generator Based on a Tree-like Scheduler.- Performance-Enhancing Bifurcations in a Self-organising Neural Network.- A Competitive Neural Network based on dipoles.- An N-Parallel Multivalued Network: Applications to the Travelling Salesman Problem.- Parallel ACS for weighted MAX-SAT.- Learning to Generate Combinatorial Action Sequences Utilizing the Initial Sensitivity of Deterministic Dynamical Systems.- BICONN: A Binary Competitive Neural Network.- SASEGASA: An Evolutionary Algorithm for Retarding Premature Convergence by Self-Adaptive Selection Pressure Steering.- Cooperative Ant Colonies for Solving the Maximum Weighted Satisfiability Problem.- Designing a Phenotypic Distance Index for Radial Basis Function Neural Networks.- The Antiquadrupolar Phase of the Biquadratic Neural Network.- Co-Evolutionary Algorithm for RBF by Self- Organizing Population of neurons.- Studying the Capacity of Grammatical Encoding to Generate FNN Architectures.- Optimal Phasor Measurement Unit Placement using Genetic Algorithms.- On the Evolutionary Inference of Temporal Boolean Networks.- Specifying evolutionary algorithms in XML.- Analysis of the Univariate Marginal Distribution Algorithm modeled by Markov chains.- Node level crossover applied to neural network evolution.- Genetic Search of Block-Based Structures of Dynamical Process Models.- Visualization of Neural Net Evolution.- Separable Recurrent Neural Networks Treated with Stochastic Velocities.- Studying the Convergence of the CFA Algorithm.- Auto-Adaptive Neural Network Tree Structure Based on Complexity Estimator.- Artificial Intelligence and Cognition.- Intelligence and Computation: A View from Physiology.- Image Understanding analysis at the Knowledge Level as a Design Task.- Morphological Clustering of the SOM for Multi-dimensional Image Segmentation.- Introducing Long Term Memory in an ANN based Multilevel Darwinist Brain.- New Directions in Connectionist Language Modeling.- Rules and Generalization Capacity Extraction from ANN with GP.- Numerosity and the Consolidation of Episodic Memory.- Rule Extraction from a Multilayer Feedforward Trained Network via Interval Arithmetic Inversion.- Necessary First-Person Axioms of Neuroconsciousness.- An Agent Based Approach of Collective Foraging.- Hybrid Architecture Based on Support Vector Machines.- A neural approach to extended logic programs.- Bioinspired Developments.- Solving SAT in Linear Time with a Neural-like Membrane System.- An Exponential-Decay Synapse Integrated Circuit For Bio-inspired Neural Networks..- A high level synthesis of an auditory mechanical to neural transduction circuit..- Restriction Enzyme Computation.- Neurally Inspired Mechanisms for the Dynamic Visual Attention Map Generation Task.- A Model of Dynamic Visual Attention for Object Tracking in Natural Image Sequences.- Neural competitive structures for segmentation based on motion features.- Background Pixel Classification for Motion Detection in Video Image Sequences.- COBRA: An Evolved Online Tool for Mammography Interpretation.- CBA generated receptive fields implemented in a Facial expression recognition task.- A Hybrid Face Detector based on an Asymmetrical Adaboost Cascade Detector and a Wavelet-Bayesian- Detector.- Neural Net Generation of Facial Displays in Talking Heads.
「Nielsen BookData」 より
