Results 51 to 60 of about 277,175 (273)
Deep Unfolding Based Space-Time Adaptive Processing Method for Airborne Radar
Leida xuebao, 2022 The Sparse Recovery Space-Time Adaptive Processing (SR-STAP) method can use a small number of training range cells to effectively suppress the clutter of airborne radar.
Hangui ZHU +4 more
doaj +1 more source
Glymphatic Dysfunction Reflects Post‐Concussion Symptoms: Changes Within 1 Month and After 3 Months
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Mild traumatic brain injury (mTBI) may alter glymphatic function; however, its progression and variability remain obscure. This study examined glymphatic function following mTBI within 1 month and after 3 months post‐injury to determine whether variations in glymphatic function are associated with post‐traumatic symptom severity ...
Eunkyung Kim +3 more
wiley +1 more source
IEEE Access, 2017 This paper addresses the recovery and demixing problem of signals that are sparse in some general dictionary. Involved applications include source separation, image inpainting, super-resolution, and restoration of signals corrupted by clipping ...
Fei Wen +5 more
doaj +1 more source
UAV-Mounted Mobile Base Station Placement via Sparse Recovery
IEEE Access, 2020 In order to deploy minimum number of unmanned aerial vehicle (UAV)-mounted mobile base stations (MBSs) to service all given ground terminals, this paper proposes an MBS placement based on sparse recovery (MBS-PBSR) algorithm.
Min Huang +3 more
doaj +1 more source
An Armijo-Type Hard Thresholding Algorithm for Joint Sparse Recovery
IEEE Access, 2021 Joint sparse recovery (JSR) in compressed sensing simultaneously recovers sparse signals with a common sparsity structure from their multiple measurement vectors obtained through a common sensing matrix.
Lili Pan, Xunzhi Zhu
doaj +1 more source
Recovery of Sparse Signals Using Multiple Orthogonal Least Squares [PDF]
, 2015 We study the problem of recovering sparse signals from compressed linear measurements. This problem, often referred to as sparse recovery or sparse reconstruction, has generated a great deal of interest in recent years.
Li, Ping, Wang, Jian
core
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective To investigate the value of constructing models based on habitat radiomics and pathomics for predicting the risk of progression in high‐grade gliomas. Methods This study conducted a retrospective analysis of preoperative magnetic resonance (MR) images and pathological sections from 72 patients diagnosed with high‐grade gliomas (52 ...
Yuchen Zhu +14 more
wiley +1 more source
IEEE Transactions on Information TheoryAccepted by IEEE Transactions on Information ...
Liyang Lu +4 more
openaire +4 more sources
Blind Phase Calibration In Sparse Recovery
EUSIPCO - 21st European Signal Processing Conference - 2013, 2013 Publication in the conference proceedings of EUSIPCO, Marrakech, Morocco ...
Bilen, Cagdas +3 more
openaire +2 more sources
Annals of Clinical and Translational Neurology, EarlyView.ABSTRACT Objective Considerable efforts have been dedicated to developing effective treatments for post‐stroke executive impairment (PSEI), among which repetitive transcranial magnetic stimulation (rTMS) has shown great potential. This study aimed to investigate the therapeutic effects of high‐frequency rTMS on working memory (WM) and response ...
Mengting Lao +6 more
wiley +1 more source