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Online system identification in Silverbox by minimising free energy

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Online Nonlinear System Identification

The goal is infer parameters in a model that can predict future output, given new input. We are testing the following models:

These models are standard in the control systems community. Typically, (recursive) least-squares or some other form of frequentist estimation is used. In this repo, we employ Free Energy Minimisation.

We run a series of verification experiments and a validation experiment on the Silverbox data set from the Nonlinear Benchmark.

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