TY - JOUR
T1 - Atomic norm minimization for decomposition into complex exponentials and optimal transport in Fourier domain
AU - Condat, Laurent
N1 - KAUST Repository Item: Exported on 2020-10-01
PY - 2020/7/13
Y1 - 2020/7/13
N2 - This paper is devoted to the decomposition of vectors into sampled complex exponentials; or, equivalently, to the information over discrete measures captured in a finite sequence of their Fourier coefficients. We study existence, uniqueness, and cardinality properties, as well as computational aspects of estimation using convex semidefinite programs. We then explore optimal transport between measures, of which only a finite sequence of Fourier coefficients is known.
AB - This paper is devoted to the decomposition of vectors into sampled complex exponentials; or, equivalently, to the information over discrete measures captured in a finite sequence of their Fourier coefficients. We study existence, uniqueness, and cardinality properties, as well as computational aspects of estimation using convex semidefinite programs. We then explore optimal transport between measures, of which only a finite sequence of Fourier coefficients is known.
UR - http://hdl.handle.net/10754/664381
UR - https://linkinghub.elsevier.com/retrieve/pii/S0021904520300927
UR - http://www.scopus.com/inward/record.url?scp=85087987162&partnerID=8YFLogxK
U2 - 10.1016/j.jat.2020.105456
DO - 10.1016/j.jat.2020.105456
M3 - Article
SN - 1096-0430
VL - 258
SP - 105456
JO - Journal of Approximation Theory
JF - Journal of Approximation Theory
ER -