Unscented Tobit Kalman filtering for switched nonlinear systems with censored measurement

Jiajia Li; Guoliang Wei; Wangyan Li

doi:10.1016/j.amc.2022.127327

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Unscented Tobit Kalman filtering for switched nonlinear systems with censored measurement

Jiajia Li Guoliang Wei Wangyan Li

Year: 2022 Journal: Applied Mathematics and Computation Vol: 431 Pages: 127327-127327 Publisher: Elsevier BV

DOI: 10.1016/j.amc.2022.127327

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Keywords:

Tobit model Censoring (clinical trials) Kalman filter Nonlinear system Mathematics Bayesian probability Algorithm Control theory (sociology) Computer science Statistics Artificial intelligence

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Target Tracking and Data Fusion in Sensor Networks

Physical Sciences → Computer Science → Artificial Intelligence

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Unscented Tobit Kalman filtering for switched nonlinear systems with censored measurement

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