COOKIES: By using this website you agree that we can place Google Analytics Cookies on your device for performance monitoring. |
University of Cambridge > Talks.cam > Isaac Newton Institute Seminar Series > On Janashia-Lagvilava method of matrix spectral factorisation
On Janashia-Lagvilava method of matrix spectral factorisationAdd to your list(s) Download to your calendar using vCal
If you have a question about this talk, please contact INI IT. This talk has been canceled/deleted 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. This talk is included in these lists:This talk is not included in any other list Note that ex-directory lists are not shown. |
Other listsStephen Cowley's Meetings John Ray Society Cambridge University Global Health Student InitiativeOther talksAll kinds of JNK: How one kinase can be an oncogene, tumour suppressor and apoptotic mediator Cyclically Covering Subspaces in F 2 to the n G I TAYLOR LECTURE - The Silent Flight of the Owl The Imaginaries We Were Born Into (Global Imaginaries through the Ages) Welcome from David Abrahams (Isaac Newton Institute) Understanding dynamic crack growth in structured systems with the Wiener-Hopf technique: Lecture 2 |