NDLI: Dynamics of the Amari-Takeuchi competitive learning model

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Volume ii - 1991

Estimation of generalization capability by combination of new information criterion and cross validation

Learning of category boundaries based on inverse recall by multilayer neural network

A fast online learning algorithm for recurrent neural networks

A non-iterative method for training feedforward networks

Comparison of perceptron training by linear programming and by the perceptron convergence procedure

Mean-variance backpropagation: a connectionist learning algorithm with a selective attention mechanism

Learning sequential structure with recurrent pRAM nets

Induction of neural networks for parallel binary operations

A superior error function for training neural networks

Flash learning for a multilayer network

An unsupervised hyperspheric multilayer feedforward neural network classifier

Characteristics of the associative memory trained by the learning-unlearning algorithm

Genetic reinforcement learning for neural networks

Generalization in feed forward neural networks

Learning explicit rules in a neural network

Minimum-cost Ho-Kashyap associative processor for piecewise-hyperspherical classification

Continuous-time temporal back-propagation

Relating logical neural network to conventional models of computation

Connectionist generalization for production: an example from GridFont

Training of a three-layer dynamical recurrent neural network for nonlinear input-output mapping

Hybrid learning in expert networks

Back propagation simulations using limited precision calculations

The capacity of a two layer network with binary weights

How Gaussian radial basis functions work

Multilayer feedforward networks can learn strange attractors

Double backpropagation increasing generalization performance

ART 2-A: an adaptive resonance algorithm for rapid category learning and recognition

On the capacity and generalisation ability of more realistic neurons

A Frobenius approximation reduction method (FARM) for determining optimal number of hidden units

Optimal learning algorithm in bidirectional associative memories

Local minima and back propagation

Reduction of interconnection weights in higher order associative memory networks

Learning in analog Hopfield networks

Self organizing modular neural networks

A comparison of two eigen-networks

Improved rate of convergence in Kohonen neural network

Application of GRG2 for training neural networks

Strategies of unsupervised learning for a parallel parsing architecture

Optimal pruning of neural tree networks for improved generalization

NETCLASS-a fresh look at connectionist category formation

A neural net model of normal and dyslexic spelling

Dynamics of the Amari-Takeuchi competitive learning model

Segmentation and binding in an oscillatory neural network

Synchronized oscillations during cooperative feature linking in visual cortex

Dynamic properties of neural network with adapting synapses

On a neural network with synaptic weight having double minimum potential

The Kanerva memory is stable

Second-order recurrent neural networks for grammatical inference

Stability of image processing neuro chips: spatial and temporal

Continuum model for quadratic memories

On the capacity of a Markov-chain encoded associative memory

On the complexity of computing equilibria for nonsymmetric analog networks

The local backward-forward algorithm

Hardware annealing for fast retrieval of optimal solutions in Hopfield neural networks

Period-doublings to chaos in a simple neural network

Global dynamics in neural networks. III

Higher degree error backpropagation in cross-coupled Hopfield nets

Turing equivalence of neural networks with second order connection weights

Reliability characteristics of Hebbian-type associative memories in network implementation

The autoregressive backpropagation algorithm

Neural-net method for dual subspace pattern recognition

On optimal adaptive classifier design criterion

Using the symmetries of a multi-layered network to reduce the weight space

Genetic generation of both the weights and architecture for a neural network

Using LMS trees for imaging processing

Fuzzy ART: an adaptive resonance algorithm for rapid, stable classification of analog patterns

Design of unsupervised classifier

Error propagation and supervised learning in adaptive resonance networks

On fuzzy neuron models

Associative memory networks, fault-tolerance and coding theory

Using stereographic projection as a preprocessing technique for Upstart

Fault tolerance of pruned multilayer networks

Learning to generate subgoals for action sequences

Optimal dimensioning of counterpropagation neural networks

Fuzzy rule extraction from a multilayered neural network

The augmented ART1 neural network

Information theoretic derivation of network architecture and learning algorithms

An ART2-TPM neural network for automatic pattern classification

Using CNLS-net to predict the Mackey-Glass chaotic time series

A neural network for interpretation of multi-meaning words

The design of multi-layer perceptrons using building blocks

Analysis of the effects of quantization in multi-layer neural networks using a statistical model

Contrastive Hebbian learning and the traveling salesman problem

A k-nearest neighbor artificial neural network classifier

Self-organizing neural network for spatio-temporal patterns

Autoassociative memory with 'inverted pyramid' logic networks

Unsupervised clustering with growing cell structures

Recurrent multilayer perceptron for nonlinear system identification

Temporal processing with connectionist networks

An integrated neurocomputing system

Encoding and classification in a model of olfactory cortex

Semi-local units for prediction

Adaptive transfer functions (backpropagation neural nets)

Cooperation of neural nets and task decomposition

Frequency based computation in neural networks

A biological approach to plasticity in artificial neural networks

A mapping neural network using unsupervised and supervised training

Recurrent and feedforward backpropagation for time independent pattern recognition

Dimension reduction, generalized deformable models and the development of occularity and orientation

Sensory segmentation by neural oscillators

Spatiotemporal correlation in the cerebellum

Unsupervised learning for the visual cortex (layer IV): model and simulations

Neural network approach to maintenance and termination of central pattern generation

Topography and ocular dominance can arise from distributed patterns of activity

A neural model suggesting how speech spectra may be represented by the nervous system

Adaptive matched filtering in peripheral nervous system

Dynamic model-based controller in the brain

An information theoretical interpretation of neuronal activities

Ontogenetic development of retinotopy and of ocular dominance columns

Neurodynamic approach to odor processing

Complex oscillations and chaos in a simple neuron model

Differentiation processing of linear and nonlinear information in retinal neural network

Evolving neural network controllers for unstable systems

Towards practical control design using neural computation

Knowledge of knowledge and intelligent experimentation for learning control

Prejudicial searches and the pole balancer

Integrated approximation and non-convex optimization using radial basis function networks

Learning to control: some practical experiments with neural networks

A structure by which a recurrent neural network can approximate a nonlinear dynamic system

Quadrupedal walking using trained and untrained neural models

Nadine-a feedforward neural network for arbitrary nonlinear time series

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Adaptive neural network control with frequency-shaped optimal output feedback

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Neural modeling and control of a distillation column

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Global optimization of a neural network-hidden Markov model hybrid

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A neural network algorithm for longitudinal motion stereo

Robust aircraft classification using moment invariants, neural network, and split inversion learning

A neural network for motion computation

A selective attention neural network for invariant recognition of distorted objects

Novel preprocessing techniques as an aid to hand-printed character recognition

Perception of illusory solid object with binocular viewing

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Neural classifiers using loss functions

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Efficient activation functions for the back-propagation neural network

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A neurointelligence: multisignificance images and neurocomputing

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Feature map learning with partial training data

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An adaptive training algorithm for layered perceptron type neural networks

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A neural network that learns to do hyphenation

Input data redundancy in interpolation-based neural nets

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Convergence analysis for a class of neural networks

Iterative methods for neural network design

Feature detectors and difference operators in BP networks

Tuning of learning rate and momentum on backpropagation

A study on a tuning method of neural network

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A clustering algorithm for implementation of RBF technique

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An algorithm for training multilayer perceptrons

Representation of information in a neural network using psychophysical functions and the maximum entropy formalism

Experimental parameter studies for the CMAC neural network

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Neural networks that learn state space trajectories by 'Hebbian' rule

Backtracking dynamics for a Hopfield-style network

Topological analysis of infinite learning automata. II. Training dynamics

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A rigorous result about the off-line learning approximation

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Measuring the effects of normalizing weight vectors on the self-organizing map

Dynamic properties of an asymmetrical non-stationary neural net

Effects of limited precision weight values on the accuracy of feedforward networks

Asynchronous learning dynamics in massively parallel recurrent neural networks

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A neural network implementation of adaptive BAM

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A mapping approach for designing neural sub-nets

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Volume i - 1991

1990 IJCNN International Joint Conference on Neural Networks

International 1989 Joint Conference on Neural Networks

Dynamics of the Amari-Takeuchi competitive learning model

Content Provider	IEEE Xplore Digital Library
Author	Troyer, T.
Copyright Year	1991
Description	Author affiliation: Dept. of Math., California Univ., Berkeley, CA, USA (Troyer, T.)
Abstract	A rigorous analysis of an analog version of the Amari-Takeuchi (1978) theory of self-organization of category detecting nerve cells is given. Convergence of the learning is proven by constructing a Lyapunov function for the learning dynamics in a convenient set of coordinates. This function has separate terms reflecting the Hebbian learning and lateral inhibition components of the theory. This facilitates a theoretic characterization of the categories formed by the model. Also proposed is a different network interpretation of the equations, with the outputs implicit functions of the inputs.
Starting Page	237
Ending Page	242
File Size	326250
Page Count	6
File Format	PDF
ISBN	0780301641
DOI	10.1109/IJCNN.1991.155344
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1991-07-08
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Neurons Lyapunov method Hebbian theory Nonlinear equations Mathematical model Mathematics Electronic mail Convergence Differential equations Brain modeling
Content Type	Text
Resource Type	Article

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