A New Linear Regression Kalman Filter with Symmetric Samples

Nonlinear filtering is of great significance in industries. In this work, we develop a new linear regression Kalman filter for discrete nonlinear filtering problems. Under the framework of linear regression Kalman filter, the key step is minimizing the Kullback–Leibler divergence between standard no...

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Auteurs principaux: Xiuqiong Chen, Jiayi Kang, Mina Teicher, Stephen S.-T. Yau
Format: article
Langue:EN
Publié: MDPI AG 2021
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Accès en ligne:https://doaj.org/article/91b554243a86435383eb991227c7f9c4
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