Clustering analysis of human finger grasping based on SOM neural network model
SOM (Self-organizing Maps) model was introduced to cluster and analyse on the human grasping activities of GloveMAP based on data reduction of the initial grasping data.By acquiring the data reduction of the initial hand grasping data of the several objects, it will be going to be functioned as the...
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| 主要な著者: | , , , |
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| フォーマット: | 論文 |
| 言語: | English |
| 出版事項: |
IJENS Publishers
2014
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| 主題: | |
| オンライン･アクセス: | http://repo.uum.edu.my/10665/1/1.pdf http://repo.uum.edu.my/10665/ http://www.ijens.org/IJMME%20Vol%2014%20Issue%2001.html |
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| 要約: | SOM (Self-organizing Maps) model was introduced to cluster and analyse on the human grasping activities of GloveMAP based on data reduction of the initial grasping data.By acquiring the data reduction of the initial hand grasping data of the several objects, it will be going to be functioned as the inputs to the SOM model.After the iterative learning of net-trained, all data of the trained network will be simulated and finally self-organized.The output results of models’ are farthest approached to the reality in 3-dimensional grasping features.The experimental result of the simulation signal will generate the simulate result of the grasping features from the selected object.The whole experiment of grasping features is derived into three features/groups and the results are
satisfactory. |
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