New Trends in Neural Computation: International Workshop on Artificial Neural Networks, IWANN'93, Sitges, Spain, June 9-11, 1993. ProceedingsSpringer Science & Business Media, 1993 M05 27 - 746 páginas Neural computation arises from the capacity of nervous tissue to process information and accumulate knowledge in an intelligent manner. Conventional computational machines have encountered enormous difficulties in duplicatingsuch functionalities. This has given rise to the development of Artificial Neural Networks where computation is distributed over a great number of local processing elements with a high degree of connectivityand in which external programming is replaced with supervised and unsupervised learning. The papers presented in this volume are carefully reviewed versions of the talks delivered at the International Workshop on Artificial Neural Networks (IWANN '93) organized by the Universities of Catalonia and the Spanish Open University at Madrid and held at Barcelona, Spain, in June 1993. The 111 papers are organized in seven sections: biological perspectives, mathematical models, learning, self-organizing networks, neural software, hardware implementation, and applications (in five subsections: signal processing and pattern recognition, communications, artificial vision, control and robotics, and other applications). |
Contenido
Biophysics of Neural Computation Invited Paper | 1 |
Integrated Learning in Rana Computatrix | 12 |
A Model for Centering Visual Stimuli Through Adaptive Value Learning | 20 |
A Model for the Development of Neurons Selective to Visual Stimulus Size | 24 |
An Invariant Representation Mechanism After Presynaptic Inhibition | 30 |
The Pancreatic BCell as a VoltageControlled Oscillator | 37 |
Approximation of the Solution of the Dendritic Cable Equation by a Small Series of Coupled Differential Equations | 43 |
A Neural Network Model Inspired in Global Appreciations About the Thalamic Reticular Nucleus and Cerebral Cortex Connectivity | 49 |
Realistic Simulation Tool for Early Visual Processing Including Space Time and Colour Data | 370 |
Language Supported Storage and Reuse of Persistent Neural Network Objects | 376 |
Flexible Operating Environment for Matrix Based Neurocomputers | 382 |
A Parallel Implemenation of Kohonens SelfOrganizing Maps on the Smart Neurocomputer | 388 |
Simulation of Neural Networks in a Distributed Computing Environment Using NeuroGraph | 394 |
A Genetic Approach | 399 |
Hardware Implementations of Artificial Neural Networks Invited Paper | 405 |
A Neural Network Chip Using CPWM Modulation | 420 |
HighOrder Recurrence and Logical Learning | 55 |
McCullochs Neurons Revisited | 63 |
Biologically Motivated Approach to Face Recognition | 68 |
A Psychobiological Model | 78 |
A Neural State Machine for Iconic Language Representation | 84 |
Variable Binding Using Serial Order in Recurrent Neural Networks | 90 |
Region of Influence ROI Networks Model and Implementation | 96 |
A Node Splitting Algorithm that Reduces the Number of Connections in a Hamming Distance Classifying Network | 102 |
A High Order Neural Model | 108 |
HigherOrder Networks for the Optimization of Block Designs | 114 |
Neural Bayesian Classifier | 119 |
Constructive Methods for a New Classifier Based on a RadialBasisFunction Neural Network Accelerated by a Tree | 125 |
Practical Realization of a Radial Basis Function Network for handwritten Digit Recognition | 131 |
Design of Fully and Partially Connected Random Neural Networks for Pattern Completion | 137 |
Representation and Recognition of Regular Grammars by Means of SecondOrder Recurrent Neural Networks | 143 |
Connectionist Models for Syllabic Recognition in the Time Domain | 149 |
Sparsely Interconnected Artificial Neural Networks for Associative Memories | 155 |
Dynamic Analysis of Networks of Neural Oscillators | 161 |
Optimised Attractor Neural Networks with External Inputs | 167 |
An Application to Artificial Neural Networks | 173 |
Genetic Synthesis of DiscreteTime Recurrent Neural Network | 179 |
Optimization of a Competitive Learning Neural Network by Genetic Algorithms | 185 |
Adaptive Models in Neural Networks | 193 |
SelfOrganizing Grammar Induction Using a Neural Network Model | 198 |
The Role of Forgetting in Efficient Learning Strategies for SelfOrganising DiscriminatorBased Systems | 204 |
Simulation of Stochastic Regular Grammars Through Simple Recurrent Networks | 210 |
Local Stochastic Competition and Vector Quantization | 216 |
MHC An Evolutive Connectionist Model for Hybrid Training | 223 |
FastConvergence Learning Algorithms for MultiLevel and Binary Neurons and Solution of Some Image Processing Problems | 230 |
Invariant Object Recognition using Fahlman and Lebieres Learning Algorithm | 237 |
Realization of Surjective Correspondence in Artificial Neural Network Trained by Fahlman and Lebieres Learning Algorithm | 243 |
Bimodal Distribution Removal | 249 |
A Simplified Artmap Architecture for RealTime Learning | 255 |
A Reinforcement Learning Algorithm Comparison with Dynamic Programming | 261 |
Increased Complexity Training | 267 |
Optimized Learning and Improving the Evolution of Piecewise Linear Separation Incremental Algorithms | 272 |
A Method of Pruning Layered FeedForward Neural Networks | 278 |
Tests of Different Regularization Terms in Small Networks | 284 |
On the Distribution of Feature Space in SelfOrganising Mapping and Convergence Accelerating by a Kalman Algorithm | 291 |
A Learning Algorithm to Obtain SelfOrganizing Maps Using Fixed Neighbourhood Kohonen Networks | 297 |
A factorial Correspondence Analysis | 305 |
Dynamics of SelfOrganized Feature Mapping | 312 |
Comparative Study of SelfOrganizing Neural Networks | 316 |
A Genetic Algorithm for Optimizing Topology and Weights in Neural Network Design | 322 |
Vector Quantization and Projection Neural Network | 328 |
Constructive Design of LVQ and DSM Classifiers | 334 |
An Improvement on LVQ Algorithms to Create Classes of Patterns | 340 |
NonGreedy Adaptive Vector Quantizers | 346 |
Hybrid Programming Environments Invited Paper | 351 |
Automatic Generation of C++ Code for Neural Network Simulation | 358 |
An ObjectOriented Artificial Neural Network Simulation Tool | 364 |
Hardware Implementation of a Neural Network for High Energy Physics Application | 426 |
An Array Processor Architecture for Neural Networks | 432 |
Limitation of Connectionism in MLP | 441 |
High Level Synthesis of Neural Network Chips | 448 |
Applications in Chemical Physics | 454 |
A Model Based Approach to the Performance Analysis of MultiLayer Networks Realised in Linear Systolic Arrays | 459 |
The Temporal NoisyLeaky Integrator Neuron with Additional Inhibitory Inputs | 465 |
Architectures for SelfLearning Neural Network Modules | 471 |
The Generic Neuron Architectural Framework for the Automatic Generation | 476 |
A Rise Architecture to Support Neural Net Simulation | 482 |
Hardware Design for SelfOrganizing Feature Maps with Binary Input Vectors | 488 |
The Kolmogerov Signal Processor Invited Paper | 494 |
Projectivity Invariant Pattern Recognition with HighOrder Neural Networks | 513 |
Rejection of Incorrect Answers from a Neural Net Classifier | 519 |
Nonlinear Time Series Modeling by Competitive Segmentation of State Space | 525 |
Identification and Prediction of NonLinear Models with Recurrent Neural Network | 531 |
Use of Unsupervised Neural Network for Classification of Blood Pressure Time Series | 536 |
Application of Artificial Neural Networks to Chest Image Classification | 542 |
Combination of SelfOrganizing Maps and Multilayer Perceptrons for Speaker Independent Isolated Word Recognition | 550 |
An Industrial Application of Neural Networks to Natural Textures Classification | 556 |
Use of a Layered Neural Nets as a Display Method for NDimensional Distributions | 563 |
MLP Modular Versus YPREL Classifiers | 569 |
How Many Hidden Neurons are Needed to Recognize a Symmetrical Pattern? | 575 |
Hopfield Neural Network for Routing | 583 |
Neural Network Routing Controller for Communication Parallel Multistage Interconnection Networks | 593 |
Adaptive Routing Using Cellular Automata | 599 |
Optimal Blind Equalization of Gaussian Channels | 605 |
Noise Prediction in Urban Traffic by a Neural Approach | 611 |
A Connectionist Approach to the Correspondence Problem in Computer Vision | 620 |
SelfOrganizing Feature Maps for Image Segmentation | 626 |
Recognition of Fractal Images Using a Neural Network | 632 |
Feed Forward Network for Vehicle License Character Recognition | 638 |
Interpretation of Optical Flow Through Complex Neural Network | 645 |
CT Image Segmentation by SelfOrganizing Learning | 651 |
Texture Image Segmentation Using a Modified Hopfield Network | 657 |
Image Compression with SelfOrganizing Networks | 664 |
Neural Networks as Direct Adaptive Controllers | 670 |
A Neural Adaptive Controller for a Turbofan Exhaust Nozzle | 676 |
FeedForward Neural Networks for Bioreactor Controller | 682 |
Learning Networks for Process Identification and Associative Action | 688 |
OnLine Performance Enhancement of a Behavioral Neural Network Controller | 694 |
An Architecture for Implementing Control and Signal Processing Neural Networks | 702 |
Adaptive Planning Using Weightless Systems | 708 |
Stock Prices and Volume in an Artificial Adaptive Stock Market | 714 |
Application of the Fuzzy Artmap Neural Network Architecture to Bank Failure Predictions | 720 |
OnLine Beauty Selection of Flowers | 726 |
An Adaptive Information Retrieval System Based on Neural Networks | 732 |
Software Pattern EEG Recognition After a Wavelet Transform by a Neural Network | 738 |
| 744 | |
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New Trends in Neural Computation: International Workshop on Artificial ... Jose Mira,Joan Cabestany,Alberto Prieto Sin vista previa disponible - 2014 |
Términos y frases comunes
activation adaptive application approach architecture Artificial Neural Networks backpropagation binary cells classification clusters complex components connectionist connections convergence corresponding defined distance distribution dynamics environment equation error evaluation example Figure filter function Genetic Algorithms Hamming distance hardware hidden layer hidden units IEEE implementation initial input pattern input vector iterations Kohonen learning algorithm linear matrix memory method modules multilayer perceptron Neural Computation neural net neurocomputer neurons node noise non-linear number of neurons obtained optical flow optimal output layer output unit parallel parallel computers parameters perceptron performance phase pixels pRAM presented problem processor programming proposed prototypes receptive fields recognition representation represented retina Rumelhart samples segmentation self-organizing Self-Organizing Map shows signal simulation solution space structure supervised learning switch synaptic threshold topology training set variables Vector Quantization VLSI weights yprel