Retrieval Property of Associative Memory Based on Inverse Function Delayed Neural Networks(Nonlinear Problems)
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概要
- 論文の詳細を見る
Self-connection can enlarge the memory capacity of an associative memory based on the neural network. However, the basin size of the embedded memory state shrinks. The problem of basin size is related to undesirable stable states which are spurious. If we can destabilize these spurious states, we expect to improve the basin size. The inverse function delayed (ID) model, which includes the Bonhoeffer-van der Pol (BVP) model, has negative resistance in its dynamics. The negative resistance of the ID model can destabilize the equilibrium states on certain regions of the conventional neural network. Therefore, the associative memory based on the ID model, which has self-connection in order to enlarge the memory capacity, has the possibility to improve the basin size of the network. In this paper, we examine the fundamental characteristics of an associative memory based on the ID model by numerical simulation and show the improvement of performance compared with the conventional neural network.
- 社団法人電子情報通信学会の論文
- 2005-08-01
著者
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Hayakawa Yoshihiro
Laboratory For Brainware Systems Laboratory For Nanoelectronics And Spintronics Research Institute O
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Hayakawa Yoshihiro
Tohoku Univ. Sendai‐shi Jpn
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LI Hongge
School of Engineering, Tohoku University
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LI Hongge
Laboratory for Brainware Systems, Laboratory for Nanoelectronics and Spintronics, Research Institute
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NAKAJIMA Koji
Laboratory for Brainware Systems, Laboratory for Nanoelectronics and Spintronics, Research Institute
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Hayakawa Yoshihiro
Laboratory For Brainware Reseach Institute Of Electrical Comunication Tohoku University:laboratory F
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Li Hongge
School Of Engineering Tohoku University
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Nakajima Koji
Tohoku Univ. Sendai‐shi Jpn
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Nakajima Koji
Laboratory For Brainware Reseach Institute Of Electrical Comunication Tohoku University:laboratory F
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