Unsupervised learning in second-order neural networks for motion analysis
This paper demonstrates how unsupervised learning based on Hebb-like mechanisms is sufficient for training second-order neural networks to perform different types of motion analysis. The paper studies the convergence properties of the network in several conditions, including different levels of nois...
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Main Authors: | , |
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Format: | Article |
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Elsevier
2011
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Online Access: | http://eprints.um.edu.my/5670/ https://doi.org/10.1016/j.neucom.2010.09.023 |
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