Results 21 to 30 of about 66,013 (262)
Sparse signal recovery from modulo observations
EURASIP Journal on Advances in Signal Processing, 2021 We consider the problem of reconstructing a signal from under-determined modulo observations (or measurements). This observation model is inspired by a relatively new imaging mechanism called modulo imaging, which can be used to extend the dynamic range ...
Viraj Shah, Chinmay Hegde
doaj +1 more source
Remote Sensing, 2022 Synthetic aperture radar (SAR) is susceptible to radio frequency interference (RFI), which becomes especially commonplace in the increasingly complex electromagnetic environments.
Yi Ding +4 more
doaj +1 more source
ISAR Imaging of Non-Stationary Moving Target Based on Parameter Estimation and Sparse Decomposition
Remote Sensing, 2023 This paper studies the inverse synthetic aperture radar imaging problem for a non-stationary moving target and proposes a non-search imaging method based on parameter estimation and sparse decomposition.
Can Liu +3 more
doaj +1 more source
Beamformers for sparse recovery
2013 IEEE International Conference on Acoustics, Speech and Signal Processing, 2013 In sparse recovery from measurement data a common approach is to use greedy pursuit reconstruction algorithms. Most of these algorithms have a correlation filter for detecting active components in the sparse data. In this paper, we show how modifications can be made for the greedy pursuit algorithms so that they use beamformers instead of the standard ...
Martin Sundin +2 more
openaire +3 more sources
On the Power of Adaptivity in Sparse Recovery [PDF]
2011 IEEE 52nd Annual Symposium on Foundations of Computer Science, 2011 The goal of (stable) sparse recovery is to recover a $k$-sparse approximation $x*$ of a vector $x$ from linear measurements of $x$. Specifically, the goal is to recover $x*$ such that ||x-x*||_p <= C min_{k-sparse x'} ||x-x'||_q for some constant $C$ and norm parameters $p$ and $q$.
Indyk, Piotr +2 more
openaire +4 more sources
An Overview on Sparse Recovery-based STAP
Leida xuebao, 2014 This paper gives a brief review on the Sparse-Recovery (SR)-based Space-Time Adaptive Processing (STAP) technique. First, the motivation for introducing sparse recovery into STAP is presented.
Ma Ze-qiang +3 more
doaj +1 more source
Recovery of Sparsely Corrupted Signals [PDF]
IEEE Transactions on Information Theory, 2012 We investigate the recovery of signals exhibiting a sparse representation in a general (i.e., possibly redundant or incomplete) dictionary that are corrupted by additive noise admitting a sparse representation in another general dictionary. This setup covers a wide range of applications, such as image inpainting, super-resolution, signal separation ...
Christoph Studer +3 more
openaire +2 more sources
Mathematics, 2019 Compressed sensing theory is widely used in the field of fault signal diagnosis and image processing. Sparse recovery is one of the core concepts of this theory.
Dingfei Jin +3 more
doaj +1 more source
High-resolution Sparse Self-calibration Imaging for Vortex Radar with Phase Error
Leida xuebao, 2021 The Orbital Angular Momentum (OAM)-based vortex radar has drawn increasing attention because of its potential for high-resolution imaging. The vortex radar high resolution imaging with limited OAM modes is commonly solved by sparse recovery, in which the
Haiyou QU +3 more
doaj +1 more source
Low-Complexity DCD-Based Sparse Recovery Algorithms
IEEE Access, 2017 Sparse recovery techniques find applications in many areas. Real-time implementation of such techniques has been recently an important area for research.
Yuriy V. Zakharov +3 more
doaj +1 more source