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Series in Communication Theory
Edited by Helmut Bölcskei
Vol. 14:
Céline Aubel,
Performance of Super-Resolution Methods in
Parameter Estimation and System Identification
1st edition 2017. XXVI, 244 pages; € 64.00.
ISBN 978-3-86628-588-0
Extracting
information from low-resolution data is a challenging task in many applications
ranging from astronomy and radar to medical imaging, microscopy, and
spectroscopy. This work examines the performance of super-resolution methods
that enable the recovery of the high-frequency information of a signal from
low-frequency, i.e., low-resolution, measurements by exploiting a priori
knowledge on the signal structure.
First, we
develop a mathematical theory of super-resolution from short-time Fourier
transform (STFT) measurements. Then, we study the problem of identifying a
linear time-varying system characterized by a discrete set of delays and
Doppler shifts, which is closely related to the super-resolution problem from
STFT measurements. Finally, we analyze the performance of so-called
high-resolution parametric subspace methods for the estimation of the spectrum
of a signal from a finite number of samples. Our results are enabled by new
bounds on the extremal singular values of complex-valued Vandermonde
matrices, with entries in the unit disk.
About the author:
Céline Aubel was born in Épinal, France,
in 1988. She received the Engineering Degree from École
Supérieure d'Électricité (Supélec), France, and the MSc in Electrical Engineering and
Information Technology from ETH Zurich, Switzerland, both in 2011, after which
she joined the Communication Technology Laboratory at ETH Zurich as a research assistant.
She graduated from ETH Zurich with the Dr. sc. degree
in 2017.
Keywords:
Series in Communication
Theory
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