The Observability in Unobservable Systems

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Authors
Kang, Wei
Xu, Liang
Zhou, Hong
Advisors
Second Readers
Subjects
Date of Issue
2022-01
Date
January 2022
Publisher
ArXiv
Language
Abstract
In this paper, we introduce the concept of observability of targeted state variables for systems that may not be fully observable. For their estimation, we introduce and exemplify a deep filter, which is a neural network specifically designed for the estimation of targeted state variables without computing the trajectory of the entire system. The observability definition is quantitative rather than a yes or no answer so that one can compare the level of observability between different sensor locations
Type
Preprint
Description
Series/Report No
Department
Applied Mathematics
Meteorology
Organization
Naval Postgraduate School
Identifiers
NPS Report Number
Sponsors
National Science Foundation under lnteragency Agreement #2202668
Naval Research Laboratory
Funding
Format
10 p.
Citation
Distribution Statement
Rights
This publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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