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Clustering analysis of human finger grasping based on SOM neural network model

Adnan, Nazrul H. and Wan, Khairunizam and AB, Shahriman and Abu Bakar, Juliana Aida (2014) Clustering analysis of human finger grasping based on SOM neural network model. International Journal of Mechanical & Mechatronics Engineering IJMME - IJENS, 14 (1). pp. 1-5. ISSN 2077-124X

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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.

Item Type: Article
Uncontrolled Keywords: Cluster Analysis, Data reduction, Fingers grasping, Grasping features, SOM neural networks
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: School of Multimedia Technology & Communication
Depositing User: Mrs. Juliana Aida Abu Bakar
Date Deposited: 21 Apr 2014 04:48
Last Modified: 27 Apr 2016 04:32
URI: http://repo.uum.edu.my/id/eprint/10665

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