Associative memory model that extracts automatically statistical information included in learning-order and recognizes objects in self organizing
| Project/Area Number |
22500216
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Sensitivity informatics/Soft computing
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| Research Institution | Oita National College of Technology |
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Principal Investigator |
KIMOTO Tomoyuki 大分工業高等専門学校, 電気電子工学科, 准教授 (30259973)
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| Co-Investigator(Kenkyū-buntansha) |
UEZU Tatsuya 奈良女子大学, 大学院・人間文化研究科, 教授 (10160160)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥3,770,000 (Direct Cost: ¥2,900,000、Indirect Cost: ¥870,000)
Fiscal Year 2012: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2011: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2010: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | Amitモデル / Hopfieldモデル / 自己組織 / 学習順番 / 分類 / 統計力学 / 混合状態 / 相関アトラクタ / 連想記憶 / Isingスピン / XYスピン / 位相振動子 / 自己組織化 / イジングスピン / 点アトラクタ / 連続アトラクタ / 連想記憶モデル / 安定性解析 / 情報抽出 / 相転移 |
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| Research Abstract |
If the observing order of observing patterns is always fixed, it might be the pattern in which same object is observed from various direction. If the randomness of the observing order is strong, the possibility that the patterns are independent mutually is high. This study examined the dependence of the attractor structure on the statistical properties of the learning order in the Amit model modified Hopfield model. We found that if the statistical properties of the learning order change, stable state can change to the appropriate attractor reflecting the relationship between memory patterns.
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Report
(4 results)
Research Products
(41 results)
