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Optimization of Training Sets For Neural-Net Processing of Characteristic Patterns From Vibrating SolidsAn artificial neural network is disclosed that processes holography generated characteristic pattern of vibrating structures along with finite-element models. The present invention provides for a folding operation for conditioning training sets for optimally training forward-neural networks to process characteristic fringe pattern. The folding pattern increases the sensitivity of the feed-forward network for detecting changes in the characteristic pattern The folding routine manipulates input pixels so as to be scaled according to the location in an intensity range rather than the position in the characteristic pattern.
Document ID
20060050064
Acquisition Source
Headquarters
Document Type
Other - Patent
Authors
Decker, Arthur J.
(NASA Glenn Research Center Cleveland, OH, United States)
Date Acquired
August 23, 2013
Publication Date
July 4, 2006
Subject Category
Cybernetics, Artificial Intelligence And Robotics
Distribution Limits
Public
Copyright
Work of the US Gov. Public Use Permitted.
Patent
US-Patent-7,072,874|NASA-CASE-LEW-17,238-1
Patent Application
US-Patent-Appl-SN-404222|US-Patent-Appl-SN-404725
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