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2015 International Joint Conference on Neural Networks (IJCNN)

2014 International Joint Conference on Neural Networks (IJCNN)

The 2013 International Joint Conference on Neural Networks (IJCNN)

The 2012 International Joint Conference on Neural Networks (IJCNN)

The 2011 International Joint Conference on Neural Networks

The 2010 International Joint Conference on Neural Networks (IJCNN)

2009 International Joint Conference on Neural Networks

2008 IEEE International Joint Conference on Neural Networks (IEEE World Congress on Computational Intelligence)

2007 International Joint Conference on Neural Networks

The 2006 IEEE International Joint Conference on Neural Network Proceedings

Proceedings. 2005 IEEE International Joint Conference on Neural Networks, 2005.

2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541)

Proceedings of the International Joint Conference on Neural Networks, 2003.

Proceedings of the 2002 International Joint Conference on Neural Networks. IJCNN'02 (Cat. No.02CH37290)

IJCNN'01. International Joint Conference on Neural Networks. Proceedings (Cat. No.01CH37222)

Proceedings of the IEEE-INNS-ENNS International Joint Conference on Neural Networks. IJCNN 2000. Neural Computing: New Challenges and Perspectives for the New Millennium

IJCNN'99. International Joint Conference on Neural Networks. Proceedings (Cat. No.99CH36339)

1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227)

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94)

Volume 7 - 1994

Volume 6 - 1994

Volume 5 - 1994

Volume 4 - 1994

Volume 3 - 1994

Volume 2 - 1994

S/sub -/ART: a modified ART 2-A algorithm with rapid intermediate learning capabilities

The use of formal measures for the training of hierarchical Kohonen maps

Unsupervised learning: the Dog Rabbit strategy

Dynamic hierarchical self-organizing neural networks

Pulse waveform synthesis using recurrent complex-valued neural networks

Nonlinear data compression and representation by combining self-organizing map and subspace rule

Training the self-organizing feature map using hybrids of genetic and Kohonen methods

A new quantitative measure of topology preservation in Kohonen's feature maps

Managing the noisy glaucomatous test data by self organising maps

The "capture effect": a new self-organizing network for "adaptive resolution" clustering in changing environments

A measure of disorder for the self-organizing map

An unsupervised neural network approach for machine-part cell design

Self-organized learning of 3 dimensions

An unsupervised neural network with a memory replacement effect

Topological preserving network by the existence of lateral feedback

Linear feature extraction in networks with lateral connections

A new competitive learning algorithm with dynamic output neuron generation

Control of annealing in minimal free energy vector quantization

Reduced risk of Kohonen's feature map non-convergence by an individual size of the neighborhood

Synthesizing neural networks by sequential addition of hidden nodes

Soft competitive learning in the extended differentiator network

Similarity analysis of molecules with self-organizing surfaces-An extension of the self-organizing map

A stochastic unsupervised competitive learning algorithm for the design of cellular manufacturing systems

Robustness of Hebbian and anti-Hebbian learning

Adventures in cubic curve fitting: two optimization techniques and their application to the training of neural networks

Towards associative non-algorithmic neural networks

Implementation of a Bayesian self-organizing neural network

Properties of learning in fuzzy ART

OSLVQ: a training strategy for optimum-size learning vector quantization classifiers

A neural network based on LVQ2 with dynamic building of the map

A learning algorithm for improving generalization ability of multi layered neural network for pattern recognition problem

Error estimation and learning data arrangement for neural networks

Instant learning for supervised learning neural networks: a rank-expansion algorithm

Estimation and learning of network parameters in semiparametric stochastic perceptron

On stochastic approximation algorithms for classes of PAC learning problems

A learning algorithm for radial basis function networks: with the capability of adding and pruning neurons

Development of feed-forward network models to predict gas consumption

A simplified statistical analysis of feedforward neural classifier

Utilization of hierarchical structure stochastic automata for neural network learning

Optimization schemes for neural network training

Characterizing numbers of n-variable logic functions implementable by threshold Adalines with integral weights between -2 and 2

An architecture for learning to behave

Generalized autoregressive prediction with application to speech coding

Enhancing the robustness of a feedforward neural network in the presence of missing data

A modified backpropagation algorithm

Supervised learning of regular languages by neural networks

Optimal learning algorithm for multilayer feedforward neural networks

Performance evaluation of a novel fault tolerance training algorithm

Paradigm for programming computers

One-shot algorithm for temporal sequences

Recurrent neural networks as pattern generators

The long and the short of it- remembering old and recent information

Learning by probabilistic Boolean networks

A weight evolution algorithm for multi-layered network

Scale-based clustering using the radial basis function network

Radial basis function networks for adaptive critic learning

Applications of binary neural networks learning to pattern classification

Some results on the exact realisation of decision regions using feed-forward networks with a single hidden layer

Exponential stability of a neural network for bound-constrained quadratic optimisation

Stochastic and deterministic neural networks with a continuous state space and a connectivity greater than two

Preprocessing of the input vectors for the linear associator neural networks

An analysis on decision boundaries in the complex back-propagation network

Hierarchical clustering with ART neural networks

Locally excitatory globally inhibitory oscillator networks: theory and application to pattern segmentation

Oscillatory behavior in a spatiotemporal neuron

Correlation between weighted sums in multi-layer perceptrons decreases under sigmoidal transformations

Stability analysis for dynamical neural network systems

Synchronization and desynchronization in locally coupled Wilson-Cowan oscillators

Noise and neuromodulatory effects in a cortical associative memory model

Convergence in neural networks with interneuronal transmission delays

Robustness of recurrent neural networks against deformation of external input patterns

Sensitivity of trained neural networks with threshold functions

On a periodically stimulated simple sign network

Use of a neural field model to derive equilibrium values for the weights of recurrent synapses

Exploring the nonlinear dynamic behavior of artificial neural networks

On the dynamics of relaxation labeling processes

A canonical form of neural dynamics in somatic reference systems

Regular and fast chaotic neural network learning for single and translation invariant pattern recognition

Stability analysis on a class of nonlinear continuous neural networks

A Lyapunov machine for stability analysis of nonlinear systems

Smooth recollection of a pattern sequence by nonmonotone analog neural networks

Stability analysis and synthesis algorithm of bidirectional associative memory

Information capacity and fault tolerance of binary weights Hopfield nets

Effect of synaptic failure on the performance of sparsely encoded Hopfield associative memory

A new local training rule for higher-order associative memories

Episodic associative memory

Recurrent correlation associative memories with multiple-value

An analysis of practical capacity of exponential bidirectional associative memory

New results of Quick Learning for Bidirectional Associative Memory having high capacity

DART1-a possible ideal building block of memory systems

Linear quantization of Hebbian-type associative memories in interconnection implementations

Sparse adaptive memory and handwritten digit recognition

EMAN: equivalent mass attraction network

Temporal associative memory with finite internal states

A new learning algorithm for bidirectional associative memory neural networks

An approach to the acquisition of a world frame using a visual associative memory

Steepest descent retrieval algorithm for autoassociative neural memory

DMAN: distributed mass attraction network

Searching algorithms of the optimal radix of exponential bidirectional associative memory

On the access by content capabilities of the LRAAM

Associative cellular memory

Prediction error of stochastic learning machine

A delta rule algorithm using double hysteresis thresholds for recurrent associative memory

Stereotyping users and tasks with associative memories

High capacity for the Hopfield neural networks

An active associative memory neural network model

Extraction of fingerprint orientation maps using a radial basis function recognition accelerator

Augmentation of an extended Kalman filter with a neural network

Non-local radial basis functions for forecasting and density estimation

Neural networks for financial market prediction

Experience with adaptive probabilistic neural networks and adaptive general regression neural networks

Some results on L/sub 1/ convergence rate of RBF networks and kernel regression estimators

Issues in benchmarking of ANN training algorithms

Connectionism without the connections

A survey of learning results for ART1 networks

Drill condition monitoring using ART-1

Fuzzy inferencing with ART networks

Adaptive resonance theory networks in the Encephalon autonomous vision system

Optimization criteria and nonlinear PCA neural networks

Nonlinear Hebbian rule: a statistical interpretation

Hebbian learning and self-association in nonlinear neural networks

Training recurrent neural networks with temporal input encodings

Temporal codes for pulsed networks

Time signatures of images

Image segmentation using pulse coupled neural networks

Reentrant pulse coupled neural networks (PCNNs)

Theories for unsupervised learning: PCA and its nonlinear extensions

Circuit design for a neuron in a pulse-coupled network

Stochastically competitive learning algorithm for vector quantizer design

Volume 1 - 1994

Proceedings of 1993 International Conference on Neural Networks (IJCNN-93-Nagoya, Japan)

[Proceedings 1992] IJCNN International Joint Conference on Neural Networks

[Proceedings] 1991 IEEE International Joint Conference on Neural Networks

IJCNN-91-Seattle International Joint Conference on Neural Networks

1990 IJCNN International Joint Conference on Neural Networks

International 1989 Joint Conference on Neural Networks

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