Evaluation of the Use of the Hopfield Neural Network Model as a Nearest-Neighbor Algorithm,
CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF ELECTRICAL AND COMPUTER ENGINEERING
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Neural network models are receiving increasing attention because of their collective computational capabilities. This reprint evaluates the use of the Hopfield neural network model in optically determining the nearest-neighbor of a binary bipolar test vector from a set of binary bipolar reference vectors. The use of the Hopfield model is compared with that of a direct technique called direct storage nearest-neighbor that accomplishes the task of nearest-neighbor determination. Keywords optical pattern recognition.