The modified extended Kalman filter based recursive estimation for Wiener nonlinear systems with process noise and measurement noise-Reference-Cited by-同舟云学术

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The modified extended Kalman filter based recursive estimation for Wiener nonlinear systems with process noise and measurement noise

Published:2020-07-30 Issue:10 Volume:34 Page:1321-1340
ISSN:0890-6327
Container-title:International Journal of Adaptive Control and Signal Processing
language:en
Short-container-title:Int J Adapt Control Signal Process

Author:

Wang Xuehai¹^ORCID,Zhu Fang²,Ding Feng³

Affiliation:

1. School of Mathematics and Statistics Xinyang Normal University Xinyang China

2. School of Educational Science Xinyang Normal University Xinyang China

3. College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao China

Funder

Nanhu Scholars Program for Young Scholars of Xinyang Normal University

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

Wiley

Subject

Electrical and Electronic Engineering,Signal Processing,Control and Systems Engineering

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/acs.3148

Reference76 articles.

1. A Low-Complexity Nonlinear Least Mean Squares Filter Based on a Decomposable Volterra Model

2. Sparse Bayesian Nonlinear System Identification Using Variational Inference

3. Data-driven approach for fault detection and isolation in nonlinear system

4. Hierarchical identification for multivariate Hammerstein systems by using the modified Kalman filter

5. Weighted Parameter Estimation for Hammerstein Nonlinear ARX Systems

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