Polar deconvolution of mixed signals
Michael P. Friedlander (University of British Columbia)
Abstract: The signal demixing problem seeks to separate the superposition of multiple signals into its constituent components. We model the superposition process as the polar convolution of atomic sets, which allows us to use the duality of convex cones to develop an efficient two-stage algorithm with sublinear iteration complexity and linear storage. If the signal measurements are random, the polar deconvolution approach stably recovers low-complexity and mutually-incoherent signals with high probability and with optimal sample complexity. Numerical experiments on both real and synthetic data confirm the theory and efficiency of the proposed approach.
Joint work with Zhenan Fan, Halyun Jeong, and Babhru Joshi at the University of British Columbia.
optimization and control
Audience: researchers in the discipline
Comments: The address and password of the zoom room of the seminar are sent by e-mail on the mailinglist of the seminar one day before each talk
One World Optimization seminar
Series comments: Description: Online seminar on optimization and related areas
The address and password of the zoom room of the seminar are sent by e-mail on the mailinglist of the seminar one day before each talk
| Organizers: | Sorin-Mihai Grad*, Radu Ioan Boț, Shoham Sabach, Mathias Staudigl |
| *contact for this listing |