Applications of artificial neural networks II: 2-5 April 1991, Orlando, Florida, Part 2
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algorithm analysis application architecture Artificial Neural Networks backpropagation backpropagation neural networks binary cell centroid CEOF Class classifiers cluster coefficients complex connections consists convergence correlation corresponding data set decoder defined described detection domain wall dynamics edge energy equation error estimation example feature extraction feature vectors filter functions Gaussian gradient Gulf Stream hidden layer hidden units identified IEEE image processing implemented initial input pattern input vector iterations leak location linear Linear Discriminant Analysis matrix measure memory model method MO SLM module neocognitron neural nets neurons nodes noise nonlinear object optimal parallel parameter plane pattern recognition peak performance pixels problem representation represented samples segmentation sensors shown in Figure side-scan sonar signal simulation space spatial statistical structure subnetworks target techniques template test set texture threshold tool wear training set trajectory transformation unsupervised learning update variables visual weights window