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Gedon, Daniel (author)
For large-scale system with tens of thousands of states and outputs the computation in the conventional Kalman filter becomes time-consuming such that Kalman filtering in large-scale real-time application is practically infeasible. A possible mathematical framework to lift the curse of dimensionality is to lift the problem in higher dimensions...
master thesis 2019
Gedon, Daniel (author), Piscaer, P.J. (author), Batselier, K. (author), Smith, C.S. (author), Verhaegen, M.H.G. (author)
An extension of the Tensor Network (TN) Kalman filter [2], [3] for large scale LTI systems is presented in this paper. The TN Kalman filter can handle exponentially large state vectors without constructing them explicitly. In order to have efficient algebraic operations, a low TN rank is required. We exploit the possibility to approximate the...
conference paper 2019