Presentation 1994/5/19
An error-correcting learning algorithm using double hysteresis thresholds for associative memory
Katsuaki Nishimura, Kenji Nakayama,
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Abstract(in English) An associative memory using fixed and variable hysteresis processes,in learning and recalling process,has been proposed by authors.This model can achieve a large memory capacity and very low noise sensitivity.However,a relation between weight change and the hysteresis threshold has not been well discussed.In this paper, a new learning algorithm is proposed,which is based on an error- correcting method.However,to avoid unstable behavior,double hysteresis thresholds are introduced.Unit states are updated using T.The error is evaluated using T+dT instead of T.This means 'over correction'.Stable and fast convergence can be obtained.Relations between η=dT, T and convergence rate and noise sensitivity are dis cussed,resulting the optimum selection for η.Furthemore,the order of presenting training data is optimized taking correlation into account.In the recalling process,a controlling method for T(n) is proposed to achieve fast recalling from noisy patterns.
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Keyword(in English) Recurrent neural networks / Hysteresis threshold / Noise performance / Error correcting method / Associative memory
Paper # NC94-12
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Committee NC
Conference Date 1994/5/19(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) An error-correcting learning algorithm using double hysteresis thresholds for associative memory
Sub Title (in English)
Keyword(1) Recurrent neural networks
Keyword(2) Hysteresis threshold
Keyword(3) Noise performance
Keyword(4) Error correcting method
Keyword(5) Associative memory
1st Author's Name Katsuaki Nishimura
1st Author's Affiliation Depertment of Electrical and Computer engineering,Faculty of Technology,Kanazawa University()
2nd Author's Name Kenji Nakayama
2nd Author's Affiliation Depertment of Electrical and Computer engineering,Faculty of Technology,Kanazawa University
Date 1994/5/19
Paper # NC94-12
Volume (vol) vol.94
Number (no) 40
Page pp.pp.-
#Pages 8
Date of Issue