2012 Fiscal Year Final Research Report
Representation of Spatio-tempral Patterns with Nonlinear Manifold and its Application to Gestrue Recognition
Project/Area Number |
23700271
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Research Category |
Grant-in-Aid for Young Scientists (B)
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Allocation Type | Multi-year Fund |
Research Field |
Sensitivity informatics/Soft computing
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Research Institution | Kyushu Institute of Technology |
Principal Investigator |
HORIO Keiichi 九州工業大学, 大学院・生命体工学研究科, 准教授 (70363413)
|
Project Period (FY) |
2011 – 2012
|
Keywords | 時空間バターン認識 / マニフォールド / 近似 / 高階自己組織化マツブ |
Research Abstract |
Spatio-temporal patterns is considered as a set of feature vectors in a feaure space called as a manifold . In this study,the manifolds were adequately approximated using graph distance based self-organizing map (GSOM),furthermore,similarity between manifolds represent peculiar forms,and the learning of higher rank SOM often becomes unstable. The learning algorithm was modified to realize a stable learning.
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Research Products
(6 results)