Nonlinear Filtering With Sporadically Missing Sensor Data-Reference-Cited by-同舟云学术

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Nonlinear Filtering With Sporadically Missing Sensor Data

Published:2023-10 Issue:10 Volume:7 Page:1-4
ISSN:2475-1472
Container-title:IEEE Sensors Letters
language:
Short-container-title:IEEE Sens. Lett.

Author:

Naik Amit Kumar¹^ORCID,Upadhyay Prabhat Kumar¹^ORCID,Magarini Maurizio²^ORCID,Singh Abhinoy Kumar³^ORCID

Affiliation:

1. Department of Electrical Engineering, Indian Institute of Technology Indore, Indore, India

2. Department of Electronics, Information and Bioengineering, Politecnico di Milano, Milano, Italy

3. Department of Electrical Engineering, Indian Institute of Technology Patna, Patna, India

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/7782634/10242612/10255261.pdf?arnumber=10255261

Reference14 articles.

1. Distributed diffusion unscented Kalman filtering based on covariance intersection with intermittent measurements

2. Modified Kalman filtering based multi-step-length gradient iterative algorithm for ARX models with random missing outputs

3. Gaussian Filtering for Simultaneously Occurring Delayed and Missing Measurements

4. Correlation Clustering Imputation for Diagnosing Attacks and Faults With Missing Power Grid Data

5. Kalman filter-based identification for systems with randomly missing measurements in a network environment

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