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Cluster Computing
Published in: Cluster Computing 2/2019

23-02-2018

Motion feature quantization of athletic sports training based on fuzzy neural network theory

Authors: Xinke Leng, Huijun Jiang, Xunhao Zou, Xiaoling Zeng

Published in: Cluster Computing | Special Issue 2/2019

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Abstract

Human frame structure model of sports movement and mathematical indication method of sports action were proposed in the thesis and the method of feature quantization and mode analysis for sports action was discussed. The method could be easily understood and realized based on graphic pattern discrimination and multimedia database technology. Meanwhile, fuzzy neural network theory was introduced to conduct action feature quantization so as to realize full automatic recognition of action feature quantization of athletic sports training. Finally, the effectiveness of action feature quantization method of athletic sports training based on fuzzy neural network theory was verified through quantitative example analysis of style feature variables of a complete set of Nanquan action.
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Metadata
Title
Motion feature quantization of athletic sports training based on fuzzy neural network theory
Authors
Xinke Leng
Huijun Jiang
Xunhao Zou
Xiaoling Zeng
Publication date
23-02-2018
Publisher
Springer US
Published in
Cluster Computing / Issue Special Issue 2/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI
https://doi.org/10.1007/s10586-018-2231-y

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