Improvement of the generalization capability for a pattern-recognition neural network that uses a Gaussian-synapse neuron model.
A method for improving the generalization capability for optical pattern recognition by use of a Gaussian-synapse neuron model is discussed. By the dispersive effect of the Gaussian function the input images are blurred and then fed into a multilayer neural network for learning and recognition. The effectiveness of this method is demonstrated in two-dimensional shift- and scale-invariant optical pattern recognition.
Lin
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Electrotechnical Laboratory, 1-1-4 Umezono, Tsukuba 305-8568, Japan.
Mori
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Watanabe
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