A NEURAL NETWORK APPROACH TO REAL-TIME PATTERN RECOGNITION
2001 ◽
Vol 15
(06)
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pp. 937-947
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Keyword(s):
This paper presents a new neural network approach to real-time pattern recognition on a given set of binary (or bipolar) sample patterns. The perceptive neuron of a binary pattern is defined and constructed as a binary neuron with a neighborhood perceptive field. Letting its hidden units be the respective perceptive neurons of the patterns, a three-layer forward neural network is constructed to recognize these patterns with minimum error probability in a noisy environment. The theoretical and simulation analyses show that the network is effective for pattern recognition and can be under strict real-time constraints.
Keyword(s):
2007 ◽
Vol 51
(1)
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pp. 45-63
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2006 ◽
Vol 117
(1)
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pp. 65-73
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Keyword(s):