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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书目详细资料
Main Authors: Adnan, Nazrul H., Wan, Khairunizam, AB, Shahriman, Abu Bakar, Juliana Aida
格式: Article
语言:English
出版: IJENS Publishers 2014
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在线阅读: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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总结: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.