Artificial neural networks : biological inspirations - ICANN 2005 : 15th International Conference, Warsaw, Poland, September 11-15, 2005 : proceedings, part I
著者
書誌事項
Artificial neural networks : biological inspirations - ICANN 2005 : 15th International Conference, Warsaw, Poland, September 11-15, 2005 : proceedings, part I
(Lecture notes in computer science, 3696)
Springer, c2005
大学図書館所蔵 全7件
  青森
  岩手
  宮城
  秋田
  山形
  福島
  茨城
  栃木
  群馬
  埼玉
  千葉
  東京
  神奈川
  新潟
  富山
  石川
  福井
  山梨
  長野
  岐阜
  静岡
  愛知
  三重
  滋賀
  京都
  大阪
  兵庫
  奈良
  和歌山
  鳥取
  島根
  岡山
  広島
  山口
  徳島
  香川
  愛媛
  高知
  福岡
  佐賀
  長崎
  熊本
  大分
  宮崎
  鹿児島
  沖縄
  韓国
  中国
  タイ
  イギリス
  ドイツ
  スイス
  フランス
  ベルギー
  オランダ
  スウェーデン
  ノルウェー
  アメリカ
注記
Includes index
内容説明・目次
内容説明
This volume is the first part of the two-volume proceedings of the International C- ference on Artificial Neural Networks (ICANN 2005), held on September 11-15, 2005 in Warsaw, Poland, with several accompanying workshops held on September 15, 2005 at the Nicolaus Copernicus University, Toru , Poland. The ICANN conference is an annual meeting organized by the European Neural Network Society in cooperation with the International Neural Network Society, the Japanese Neural Network Society, and the IEEE Computational Intelligence Society. It is the premier European event covering all topics concerned with neural networks and related areas. The ICANN series of conferences was initiated in 1991 and soon became the major European gathering for experts in those fields. In 2005 the ICANN conference was organized by the Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland, and the Nicolaus Copernicus Univ- sity, Toru , Poland. From over 600 papers submitted to the regular sessions and some 10 special c- ference sessions, the International Program Committee selected - after a thorough peer-review process - about 270 papers for publication. The large number of papers accepted is certainly a proof of the vitality and attractiveness of the field of artificial neural networks, but it also shows a strong interest in the ICANN conferences.
目次
Modeling the Brain and Cognitive Functions.- Novelty Analysis in Dynamic Scene for Autonomous Mental Development.- The Computational Model to Simulate the Progress of Perceiving Patterns in Neuron Population.- Short Term Memory and Pattern Matching with Simple Echo State Networks.- Analytical Solution for Dynamic of Neuronal Populations.- Dynamics of Cortical Columns - Sensitive Decision Making.- Dynamics of Cortical Columns - Self-organization of Receptive Fields.- Optimal Information Transmission Through Cortico-Cortical Synapses.- Ensemble of SVMs for Improving Brain Computer Interface P300 Speller Performances.- Modelling Path Integrator Recalibration Using Hippocampal Place Cells.- Coding of Objects in Low-Level Visual Cortical Areas.- A Gradient Rule for the Plasticity of a Neuron's Intrinsic Excitability.- Building the Cerebellum in a Computer.- Special Session: The Development of Cognitive Powers in Embodied Systems.- Combining Attention and Value Maps.- Neural Network with Memory and Cognitive Functions.- Associative Learning in Hierarchical Self Organizing Learning Arrays.- A Review of Cognitive Processing in the Brain.- Spiking Neural Networks.- Neuronal Behavior with Sub-threshold Oscillations and Spiking/Bursting Activity Using a Piecewise Linear Two-Dimensional Map.- On-Line Real-Time Oriented Application for Neuronal Spike Sorting with Unsupervised Learning.- A Spiking Neural Sparse Distributed Memory Implementation for Learning and Predicting Temporal Sequences.- ANN-Based System for Sorting Spike Waveforms Employing Refractory Periods.- Emergence of Oriented Cell Assemblies Associated with Spike-Timing-Dependent Plasticity.- An Information Geometrical Analysis of Neural Spike Sequences.- Perceptual Binding by Coupled Oscillatory Neural Network.- Experimental Demonstration of Learning Properties of a New Supervised Learning Method for the Spiking Neural Networks.- Single-Unit Recordings Revisited: Activity in Recurrent Microcircuits.- A Hardware/Software Framework for Real-Time Spiking Systems.- Efficient Source Detection Using Integrate-and-Fire Neurons.- Associative Memory Models.- A Model for Hierarchical Associative Memories via Dynamically Coupled GBSB Neural Networks.- Balance Algorithm for Point-Feature Label Placement Problem.- Models of Self-correlation Type Complex-Valued Associative Memories and Their Dynamics.- Recovery of Performance in a Partially Connected Associative Memory Network Through Coding.- Optimal Triangle Stripifications as Minimum Energy States in Hopfield Nets.- Models of Biological Functions.- A Biophysical Model of Decision Making in an Antisaccade Task Through Variable Climbing Activity.- Can Dynamic Neural Filters Produce Pseudo-Random Sequences?.- Making Competition in Neural Fields Suitable for Computational Architectures.- Neural Network Computations with Negative Triggering Thresholds.- A Model for Delay Activity Without Recurrent Excitation.- Neuronal Coding Strategies for Two-Alternative Forced Choice Tasks.- Learning Features of Intermediate Complexity for the Recognition of Biological Motion.- Study of Nitric Oxide Effect in the Hebbian Learning: Towards a Diffusive Hebb's Law.- Special Session: Projects in the Area of NeuroIT.- Deterministic Modelling of Randomness with Recurrent Artificial Neural Networks.- Action Understanding and Imitation Learning in a Robot-Human Task.- Comparative Investigation into Classical and Spiking Neuron Implementations on FPGAs.- HYDRA: From Cellular Biology to Shape-Changing Artefacts.- The CIRCE Head: A Biomimetic Sonar System.- Tools for Address-Event-Representation Communication Systems and Debugging.- New Ears for a Robot Cricket.- Reinforcement Learning in MirrorBot.- Evolutionary and Other Biological Inspirations.- Varying the Population Size of Artificial Foraging Swarms on Time Varying Landscapes.- Lamarckian Clonal Selection Algorithm with Application.- Analysis for Characteristics of GA-Based Learning Method of Binary Neural Networks.- Immune Clonal Selection Wavelet Network Based Intrusion Detection.- Investigation of Evolving Populations of Adaptive Agents.- Enhancing Cellular Automata by an Embedded Generalized Multi-layer Perceptron.- Intelligent Pattern Generation for a Tactile Communication System.- Self-organizing Maps and Their Applications.- Self-organizing Map Initialization.- Principles of Employing a Self-organizing Map as a Frequent Itemset Miner.- Spatio-Temporal Organization Map: A Speech Recognition Application.- Residual Activity in the Neurons Allows SOMs to Learn Temporal Order.- Ordering of the RGB Space with a Growing Self-organizing Network. Application to Color Mathematical Morphology.- SOM of SOMs: Self-organizing Map Which Maps a Group of Self-organizing Maps.- The Topographic Product of Experts.- Self Organizing Map (SOM) Approach for Classification of Power Quality Events.- SOM-Based Method for Process State Monitoring and Optimization in Fluidized Bed Energy Plant.- A New Extension of Self-optimizing Neural Networks for Topology Optimization.- A Novel Technique for Data Visualization Based on SOM.- Statistical Properties of Lattices Affect Topographic Error in Self-organizing Maps.- Increasing Reliability of SOMs' Neighbourhood Structure with a Bootstrap Process.- Computer Vision.- Artificial Neural Receptive Field for Stereovision.- Pattern Detection Using Fast Normalized Neural Networks.- Neural Network Model for Extracting Optic Flow.- A Modular Single-Hidden-Layer Perceptron for Letter Recognition.- Fast Color-Based Object Recognition Independent of Position and Orientation.- Class-Specific Sparse Coding for Learning of Object Representations.- Neural Network Based Adult Image Classification.- Online Learning for Object Recognition with a Hierarchical Visual Cortex Model.- Extended Hopfield Network for Sequence Learning: Application to Gesture Recognition.- Accurate and Robust Image Superresolution by Neural Processing of Local Image Representations.- The Emergence of Visual Object Recognition.- Implicit Relevance Feedback from Eye Movements.- Image Segmentation by Complex-Valued Units.- Cellular Neural Networks for Color Image Segmentation.- Image Segmentation Using Watershed Transform and Feed-Back Pulse Coupled Neural Network.- Adaptive Switching Median Filter with Neural Network Impulse Detection Step.- Face Recognition and Detection.- Human Face Detection Using New High Speed Modular Neural Networks.- Face Detection Using Convolutional Neural Networks and Gabor Filters.- Face Identification Performance Using Facial Expressions as Perturbation.- Discriminative Common Images for Face Recognition.- Classification of Face Images for Gender, Age, Facial Expression, and Identity.- Sound and Speech Recognition.- Classifying Unprompted Speech by Retraining LSTM Nets.- Temporal Sound Processing by Cochlear Nucleus Octopus Neurons.- A SOM Based 2500 - Isolated - Farsi - Word Speech Recognizer.- Training HMM/ANN Hybrid Speech Recognizers by Probabilistic Sampling.- Chord Classifications by Artificial Neural Networks Revisited: Internal Representations of Circles of Major Thirds and Minor Thirds.- Bioinformatics.- Biclustering Gene Expression Data in the Presence of Noise.- Gene Extraction for Cancer Diagnosis by Support Vector Machines.- High-Throughput Multi-dimensional Scaling (HiT-MDS) for cDNA-Array Expression Data.- Biomedical Applications.- Comparing Neural Network Architecture for Pattern Recognize System on Artificial Noses.- Medical Document Categorization Using a Priori Knowledge.- A Neurofuzzy Methodology for the Diagnosis of Wireless-Capsule Endoscopic Images.- Neural Network Use for the Identification of Factors Related to Common Mental Disorders.- Development and Realization of the Artificial Neural Network for Diagnostics of Stroke Type.- Special Session: Information-Theoretic Concepts in Biomedical Data Analysis.- A First Attempt at Constructing Genetic Programming Expressions for EEG Classification.- SOM-Based Wavelet Filtering for the Exploration of Medical Images.- Functional MRI Analysis by a Novel Spatiotemporal ICA Algorithm.- Early Detection of Alzheimer's Disease by Blind Source Separation, Time Frequency Representation, and Bump Modeling of EEG Signals.
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