Presentation 1997/2/6
Local Feature Learning Algorithm for Acceleration of Learning Process
Yoshihiro Hayakawa, Yasuji Sawada,
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Abstract(in English) Neural network whose connection weights can be varied is often used for learning and adaptation systems. There were proposed variety of leaning algorithms, among which "Back Propagation (BP)" is most well known. It is known,however, that BP is much slower man is expected for the "real time learning algorithm". So it is a most important pmblem to develop a fast algorithm for "Ieal time learning". Here in this paper we present a new general and simple algorithm taking account loca1 feature into the original BP algorithm. We obtaind a surprising acceleration rate by this new algorithm.
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Keyword(in English) Neural Network / Learning / accelemtion / Local Feature / BackPropagation
Paper # NLP96-130,NC96-84
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Committee NC
Conference Date 1997/2/6(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) Local Feature Learning Algorithm for Acceleration of Learning Process
Sub Title (in English)
Keyword(1) Neural Network
Keyword(2) Learning
Keyword(3) accelemtion
Keyword(4) Local Feature
Keyword(5) BackPropagation
1st Author's Name Yoshihiro Hayakawa
1st Author's Affiliation Research Institute of Electrical Communication, Tohoku Univ.()
2nd Author's Name Yasuji Sawada
2nd Author's Affiliation Research Institute of Electrical Communication, Tohoku Univ.
Date 1997/2/6
Paper # NLP96-130,NC96-84
Volume (vol) vol.96
Number (no) 511
Page pp.pp.-
#Pages 8
Date of Issue