Research and analysis of maximum likelihood recursive identification algorithm based on physical exercise behavior of obese children. Issue 3 (March 2021)

• Record Type: Journal Article
• Authors: Zhao, Huoping; Wang, Dong; Li, Dahu; Sun, Kang; Zhang, Wanjun; Gou, Xiaoping; Zhang, Feng
• Is Part Of: IOP conference series. Volume 714:Issue 3(2021)
• Publication Date: 2021-03
• Subjects: Nonlinear system -- maximum likelihood recursive identification -- identification algorithm -- research and analysis.; Earth sciences -- Periodicals; Environmental sciences -- Congresses; Environmental sciences -- Periodicals; 550.5
• DOI: 10.1088/1755-1315/714/3/032042
• Languages: English
• ISSNs: 1755-1307

Abstract

Abstract: With the decrease of physical activity, children's health problem will become an urgent problem in building a well-off society in an all-round way. There are differences in the safe heart rate of children with different physique when they exercise.This paper studies the suitable heart rate of children with different physique. Based on a maximum likelihood recursive algorithm for obese children's physical exercise behavior, a model recognition system based on the maximum likelihood recursive algorithm for obese children's physical exercise behavior is established. Finally, through MATLAB simulation analysis, the results show that fat the model recognition of MLR algorithm is consistent with the actual results, and the simulation results verify the feasibility and effectiveness of MLR algorithm.