https://github.com/biaslab/acc2022-vmpnarmax
Experiments and derivations for ACC2022 paper on variational message passing for online NARMAX identification.
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Experiments and derivations for ACC2022 paper on variational message passing for online NARMAX identification.
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ACC2022 VMP-NARMAX
Experiments and supplementary derivations for the paper entitled
"Variational message passing for online polynomial NARMAX identification"
published at the 2022 American Control Conference.
The goal is infer parameters in a polynomial NARMAX model (see ForneyLab node code) and simulate outputs. Typically, (recursive) least-squares or another form of maximum-likelihood estimation is used. In this project, we employ variational Free Energy Minimisation in the form of variational message passing on a Forney-style factor graph.
We run a series of verification experiments on data generated from a NARMAX system, comparing performance as a function of sample size, polynomial order and simulation noise.
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- Name: BIASlab
- Login: biaslab
- Kind: organization
- Email: info@biaslab.org
- Location: Eindhoven, the Netherlands
- Website: http://biaslab.org
- Repositories: 47
- Profile: https://github.com/biaslab
Bayesian Intelligent Autonomous Systems lab
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