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On Janashia-Lagvilava method of matrix spectral factorisation

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WHTW01 - Factorisation of matrix functions: New techniques and applications

Janashia-Lagvilava method is a relatively new algorithm of matrix spectral factorisation which can be applied to compute an approximate spectral factor of any matrix function (non-rational, large scale, singular) which satisfies the necessary and sufficient condition for the existence of spectral factorisation. The numerical properties of the method strongly depend on the way it is algorithmised and we propose its efficient algorithmisation. The method has already been successfully used in connectivity analysis of complex networks. The algorithm has the potential to be used in control system design and implementation for the required optimal controller computations by using frequency response data directly from measurements on real systems. It also provides a robust way of Granger causality computation for noisy singular data.

This talk is part of the Isaac Newton Institute Seminar Series series.

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