Speaker: Ivan Markovsky
Time and place: Tue, 14/05/2019 - 10:30, ELEC seminar room
Abstract: Estimation of common dynamics among several observed signals occurs in signal processing, system theory, and computer algebra problems. In this talk, we propose subspace and optimization methods for common linear time-invariant dynamics detection and estimation. First, we consider the deterministic problem of detection of common dynamics when the data is exact (noise free). Then, we consider the stochastic estimation problem when the data is corrupted by white Gaussian noise. The methods proposed have a system theoretic interpretation of finding the intersection of autonomous linear time-invariant behaviors.
Reference: I. Markovsky, T. Liu, and A. Takeda. Common dynamics estimation. Technical report, Dept. ELEC, Vrije Universiteit Brussel, 2019. http://homepages.vub.ac.be/~imarkovs/publications/common-dynamics.pdf