## Proceedings of the ... International Conference on Neural Networks, Volume 1; Volume 3; Volumes 5-7 |

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### Contents

NEURAL NETWORK HARDWARE PERFORMANCE CRITERIA 1885 | xxxi |

ADAPTIVE RESONANCE THEORY NEURAL NETWORKSINVITED SESSION | xlviii |

GRADIENT BASED FUZZY CMEANS GBFCM ALGORITHM 1626 | lxv |

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activation function adaptation applications approach approximation ARTIFICIAL NEURAL NETWORKS backpropagation algorithm Bernoulli error measure binary chromosomes classification complexity connection weights convergence data set decision boundaries defined denote distribution dynamic encoding Engineering epochs equation error function example feedforward neural networks Figure genetic algorithm given GMDP gradient descent hidden layer hidden neurons hidden nodes hidden units hyperplane IEEE implementation input pattern input vector iteration JAPAN learning algorithm learning rate learning speed linear mapping method minimization multi-valued functions multilayer multilayer perceptron network architecture neuron nonlinear number of hidden optimal output layer output neuron output units parallel parameters perceptron performance problem processor propagation proposed random RECURRENT NEURAL NETWORKS Rumelhart shown sigmoid sigmoid function simulation space squared error structure subnetworks subset success success supervised learning target Technology Theorem tion training data training patterns training set University update values