@inproceedings{91d4c3cc485c484a8b0192b07e179032,
title = "Range-space based identification of parametric linear systems",
abstract = "Range-space based identification aims at the recovery of a linear system (e.g multi-FIR channel identification for deblurring) by its output span, and constraints on its structure, often given by explicit parameterization. A key question for this inverse problem is under what conditions the recovered system is unique. When the parametrization is polynomial, algebraic geometry is a natural apparatus to analyze this problem. In this paper, we show that the collection of all non-identifiable parameters form an algebraic variety in the parameter space, which under certain conditions is nowhere dense. This allows to develop a simple numerical test to guarantee identifiability of certain parametric families of linear systems.",
keywords = "Algebraic Geometry, Blind Deconvolution, Channel Equalization, Identification",
author = "Elad Yarkony and Yuliy Baryshnikov and Yoram Bresler",
note = "Funding Information: Supported by AFOSR FA9550-10-1-05678 and FA9550-11-1-0216 (Baryshnikov, Yarkony), NSF CCF 10-18789 (Bresler, Yarkony) Publisher Copyright: {\textcopyright} 2016 IEEE.; 12th IEEE Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2016 ; Conference date: 11-07-2016 Through 12-07-2016",
year = "2016",
month = aug,
day = "1",
doi = "10.1109/IVMSPW.2016.7528192",
language = "English (US)",
series = "2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2016 IEEE 12th Image, Video, and Multidimensional Signal Processing Workshop, IVMSP 2016",
address = "United States",
}