{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:37:36Z","timestamp":1760240256571,"version":"build-2065373602"},"reference-count":25,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2019,4,18]],"date-time":"2019-04-18T00:00:00Z","timestamp":1555545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"The Research on the Evolution and Innovation of China\u2019s National Basketball Team\u2019s System and Mechanism","award":["16BTY086"],"award-info":[{"award-number":["16BTY086"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In the course of basketball training, a large number of basketball action data are generated according to the athletes\u2019 body movements. Due to the low precision of the basketball action data processed by the traditional method in basketball technical training, basketball action processing is not in place. The basketball motion data processing method, based on the mode symmetric algorithm was studied. The basketball motion detection algorithm based on symmetric difference and background reduction was used to remove the background influence of basketball movement and obtain the binary basketball action target image containing the data. On this basis, the pole symmetric mode decomposition (ESMD) method was used to modally decompose the binary basketball action target image containing the data, and the least squares method was used to optimize the elliptic (AGM) curve to realize the screening of basketball action modal data. Through the cleaning and integration of basketball action modal data, integration and data reduction basketball action modal data, the data was processed efficiently. The experimental results showed that the proposed method was a high precision and high efficiency basketball action data processing method.<\/jats:p>","DOI":"10.3390\/sym11040560","type":"journal-article","created":{"date-parts":[[2019,4,18]],"date-time":"2019-04-18T11:58:21Z","timestamp":1555588701000},"page":"560","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Basketball Action Data Processing Method Based on Mode Symmetric Algorithm"],"prefix":"10.3390","volume":"11","author":[{"given":"Fei","family":"Zhang","sequence":"first","affiliation":[{"name":"Physical Education School, Beijing Sport University, Beijing 100084, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yi","family":"Jiang","sequence":"additional","affiliation":[{"name":"Physical Education School, Beijing Sport University, Beijing 100084, China"},{"name":"School of Physical Education, Hainan Normal University, Haikou 571158, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2019,4,18]]},"reference":[{"key":"ref_1","first-page":"1","article-title":"Neutrino Mixing with Nonzero \u039813 and CP Violation in the 3-3-1 Model Based on A4 Flavor Symmetry","volume":"30","author":"Vien","year":"2015","journal-title":"Int. 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