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Can I read State Estimation of a Physical System with Unknown Governing Equations on EtoBox?
State Estimation of a Physical System with Unknown Governing Equations by Kevin Course; Prasanth B. Nair is a Physics and Astronomy article available to read on EtoBox.
What is State Estimation of a Physical System with Unknown Governing Equations about?
State estimation is concerned with reconciling noisy observations of a physical system with the mathematical model believed to predict its behaviour for the purpose of inferring unmeasurable states and denoising measurable ones^1,2^. Traditional state-estimation techniques rely on strong assumptions about the form of uncertainty in mathematical models, typically that it manifests as an additive stochastic perturbation or is parametric in nature^3^. Here we present a reparametrization trick for stochastic variational inference with Markov Gaussian processes that enables an approximate Bayesian approach for state estimation in which the equations governing how the system evolves over time are partially or completely unknown. In contrast to classical state-estimation techniques, our method learns the missing terms in the mathematical model and a state estimate simultaneously from an approximate Bayesian perspective. This development enables the application of state-estimation methods to problems that have so far proved to be beyond reach. Finally, although we focus on state estimation, the advancements to stochastic variational inference made here are applicable to a broader class of
Who reads State Estimation of a Physical System with Unknown Governing Equations?
It is typically read by researchers, students, and practitioners in Physics and Astronomy.
- Author
- Kevin Course; Prasanth B. Nair
- Publisher
- Springer Science and Business Media LLC
- Published
- 2023
- Language
- EN
- Field
- Physics and Astronomy (Physical Sciences)