Presentation 1998/6/18
A High-Speed Defect Compensation of Multi-Layer Neural Networks by the Partial Retraining
Kunihito Yamamori, Toru Abe, Susumu Horiguchi,
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Abstract(in English) In this paper, we discuss the ability of the partial-retraining scheme to compensate the neural networks with stuck-defects of the weight or the unit. The partial retraining scheme only adjusts the weights between a unit which is affected by the defect and the units in the lower by the 2-layer back-propagation algorithm. We show the performance of partialretraining scheme by some simulations. As a result, the partial-retraining scheme is about 100 times faster than the 3-layer back-propagation algorithm to compensate 0-stuck-defect of weight between the hidden layer and the output layer.
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Keyword(in English) Neural Network / Partial Retraining / Defect Compensation / Retraining
Paper # NC98-20,HIP98-11
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Committee NC
Conference Date 1998/6/18(1days)
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Registration To Neurocomputing (NC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A High-Speed Defect Compensation of Multi-Layer Neural Networks by the Partial Retraining
Sub Title (in English)
Keyword(1) Neural Network
Keyword(2) Partial Retraining
Keyword(3) Defect Compensation
Keyword(4) Retraining
1st Author's Name Kunihito Yamamori
1st Author's Affiliation Graduate School of Information Science, Japan Advanced Institute of Science and Technology()
2nd Author's Name Toru Abe
2nd Author's Affiliation Graduate School of Information Science, Japan Advanced Institute of Science and Technology
3rd Author's Name Susumu Horiguchi
3rd Author's Affiliation Graduate School of Information Science, Japan Advanced Institute of Science and Technology
Date 1998/6/18
Paper # NC98-20,HIP98-11
Volume (vol) vol.98
Number (no) 128
Page pp.pp.-
#Pages 8
Date of Issue