Compressive sensing meets time–frequency: An overview of recent advances in time–frequency processing of sparse signals
Compressive sensing is a framework for acquiring sparse signals at sub-Nyquist rates. Once
compressively acquired, many signals need to be processed using advanced techniques …
compressively acquired, many signals need to be processed using advanced techniques …
[图书][B] An invitation to compressive sensing
This first chapter formulates the objectives of compressive sensing. It introduces the
standard compressive problem studied throughout the book and reveals its ubiquity in many …
standard compressive problem studied throughout the book and reveals its ubiquity in many …
Compressive sensing applied to radar systems: an overview
MA Hadi, S Alshebeili, K Jamil… - Signal, Image and Video …, 2015 - Springer
Modern radar systems tend to utilize high bandwidth, which requires high sampling rate, and
in many cases, these systems involve phased array configurations with a large number of …
in many cases, these systems involve phased array configurations with a large number of …
A probabilistic and RIPless theory of compressed sensing
This paper introduces a simple and very general theory of compressive sensing. In this
theory, the sensing mechanism simply selects sensing vectors independently at random …
theory, the sensing mechanism simply selects sensing vectors independently at random …
Compressive sensing and structured random matrices
H Rauhut - Theoretical foundations and numerical methods for …, 2010 - degruyter.com
These notes give a mathematical introduction to compressive sensing focusing on recovery
using1-minimization and structured random matrices. An emphasis is put on techniques for …
using1-minimization and structured random matrices. An emphasis is put on techniques for …
[PDF][PDF] Compressive Sensing.
M Fornasier, H Rauhut - Handbook of mathematical methods in …, 2015 - ee301.wikidot.com
Compressive sensing is a new type of sampling theory, which predicts that sparse signals
and images can be reconstructed from what was previously believed to be incomplete …
and images can be reconstructed from what was previously believed to be incomplete …
Suprema of chaos processes and the restricted isometry property
F Krahmer, S Mendelson… - Communications on Pure …, 2014 - Wiley Online Library
We present a new bound for suprema of a special type of chaos process indexed by a set of
matrices, which is based on a chaining method. As applications we show significantly …
matrices, which is based on a chaining method. As applications we show significantly …
Time-frequency energy distributions meet compressed sensing
P Flandrin, P Borgnat - IEEE Transactions on Signal Processing, 2010 - ieeexplore.ieee.org
In the case of multicomponent signals with amplitude and frequency modulations, the
idealized representation which consists of weighted trajectories on the time-frequency (TF) …
idealized representation which consists of weighted trajectories on the time-frequency (TF) …
Identification of parametric underspread linear systems and super-resolution radar
WU Bajwa, K Gedalyahu… - IEEE Transactions on …, 2011 - ieeexplore.ieee.org
Identification of time-varying linear systems, which introduce both time-shifts (delays) and
frequency-shifts (Doppler-shifts), is a central task in many engineering applications. This …
frequency-shifts (Doppler-shifts), is a central task in many engineering applications. This …
The Faber–Krahn inequality for the short-time Fourier transform
F Nicola, P Tilli - Inventiones mathematicae, 2022 - Springer
In this paper we solve an open problem concerning the characterization of those
measurable sets Ω⊂ R 2 d that, among all sets having a prescribed Lebesgue measure, can …
measurable sets Ω⊂ R 2 d that, among all sets having a prescribed Lebesgue measure, can …