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A NeurocomputatJonal Approach
Particle Tracking by Deformable Templates
LEARNING GENERALIZATION I Poster Presentations
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accuracy activation adaptive analog applications approach approximation architecture array artificial neural network associated keywords backpropagation binary Boltzmann machine cells chip circuit classifier cluster components computational connections constraints convergence corresponding data set detection distribution dynamic thesaurus encoding equation error estimate example feature map feedforward filter function Gabor Gabor filter gradient gradient descent hidden layer hidden units Hough transform hyperspherical IEEE implementation input pattern input vector Kohonen learning algorithm learning rate learning rule linear matrix measure memory method minimize motion multiple neural network neurons nodes noise nonlinear operation optical optimal output layer parallel parameters pattern recognition perceptron performance pixels problem processor Projection Pursuit quantization recurrent neural networks Rumelhart sample segmentation self-organizing sensor shown in Figure signal simulated annealing simulation solution supervised learning surface synapses target test set threshold training set update variables vector quantization visual VLSI voltage weight vector