Presentation | 1994/5/19 Dynamic Analysis of Associative Memories and Effects of Threshold Control Kyoko Miyake, Keiko Kido, Keisuke Ikehara, Kenji Nakayama, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Associative memories,which can perform additional learning and human like associative functions,are discussed.The conventional models include the instance unit model,the activation spread model and the constraint satisfaction model.They can perform fundamental association.However,it is rather difficult to perform complicated association.Human like association functions are also difficult to be done.One of the reasons is inhibitory connections.In the third model,it is difficult to estimate the optimum sampling point.On the other hand,the proposed NN model can provide more wide range of associative functions.Furthermore,relation between the variable threshold and association is discussed.As a result,it becomes possible to estimate the optimum sampling point. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Associative memory / Additional learning / Psychology / Threshold |
Paper # | NC94-13 |
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Committee | NC |
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Conference Date | 1994/5/19(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Neurocomputing (NC) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Dynamic Analysis of Associative Memories and Effects of Threshold Control |
Sub Title (in English) | |
Keyword(1) | Associative memory |
Keyword(2) | Additional learning |
Keyword(3) | Psychology |
Keyword(4) | Threshold |
1st Author's Name | Kyoko Miyake |
1st Author's Affiliation | Kanazawa University() |
2nd Author's Name | Keiko Kido |
2nd Author's Affiliation | Hokuriku NEC Software |
3rd Author's Name | Keisuke Ikehara |
3rd Author's Affiliation | NTT |
4th Author's Name | Kenji Nakayama |
4th Author's Affiliation | Kanazawa University |
Date | 1994/5/19 |
Paper # | NC94-13 |
Volume (vol) | vol.94 |
Number (no) | 40 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |