| Autor: |
An Xuemei, Yang Rui, Alghazzawi Daniyal M., Joseph Nympha Rita |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Applied Mathematics and Nonlinear Sciences, Vol 7, Iss 2, Pp 49-58 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2444-8656 |
| DOI: |
10.2478/amns.2021.2.00088 |
| Popis: |
The paper proposes a data model analysis algorithm for human motion function based on short-term behaviour. The algorithm uses a functional data analysis (FDA) method to perform Fourier fitting on the motion data and extract the fitted approximate single period data. Finally, the algorithm depicts the internal change in the motion in the low-dimensional space. The study found that the characteristic motion data obtained by the algorithm has smooth characteristics, and the relevant case analysis also verifies the algorithm's effectiveness. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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