Results 61 to 70 of about 9,948,343 (299)
An importance sampling algorithm for generating exact eigenstates of the nuclear Hamiltonian
We endow a recently devised algorithm for generating exact eigensolutions of large matrices with an importance sampling, which is in control of the extent and accuracy of the truncation of their dimensions. We made several tests on typical nuclei using a
A Porrino +23 more
core +1 more source
Energy Preserved Sampling for Compressed Sensing MRI [PDF]
The sampling patterns, cost functions, and reconstruction algorithms play important roles in optimizing compressed sensing magnetic resonance imaging (CS-MRI). Simple random sampling patterns did not take into account the energy distribution ink-space and resulted in suboptimal reconstruction of MR images.
Zhang, Yudong +3 more
openaire +2 more sources
ABSTRACT Introduction Spinal cord infarction (SCI) is a rare but devastating myelopathy, characterized by a high disability rate and an unfavorable prognosis. It has often been underdiagnosed and misdiagnosed as idiopathic transverse myelitis (ITM). This study aimed to describe the clinical features, radiological biomarkers, treatments, and functional ...
Zeqiang Ji +13 more
wiley +1 more source
Compressed Measurements Based Spectrum Sensing for Wideband Cognitive Radio Systems
Spectrum sensing is the most important component in the cognitive radio (CR) technology. Spectrum sensing has considerable technical challenges, especially in wideband systems where higher sampling rates are required which increases the complexity and ...
Taha A. Khalaf +2 more
doaj +1 more source
Sample Distortion for Compressed Imaging
We propose the notion of a sample distortion (SD) function for independent and identically distributed (i.i.d) compressive distributions to fundamentally quantify the achievable reconstruction performance of compressed sensing for certain encoder-decoder
Davies, Mike E., Guo, Chunli
core +1 more source
Imaging via Compressive Sampling [PDF]
Image compression algorithms convert high-resolution images into a relatively small bit streams in effect turning a large digital data set into a substantially smaller one. This article introduces compressive sampling and recovery using convex programming.
openaire +1 more source
Green Compressive Sampling Reconstruction in IoT Networks [PDF]
In this paper, we address the problem of green Compressed Sensing (CS) reconstruction within Internet of Things (IoT) networks, both in terms of computing architecture and reconstruction algorithms. The approach is novel since, unlike most of the literature dealing with energy efficient gathering of the CS measurements, we focus on the energy ...
COLONNESE, Stefania +5 more
openaire +5 more sources
Impact of Asymptomatic Intracranial Hemorrhage on Outcome After Endovascular Stroke Treatment
ABSTRACT Background Endovascular treatment (EVT) achieves high rates of recanalization in acute largeāvessel occlusion (LVO) stroke, but functional recovery remains heterogeneous. While symptomatic intracranial hemorrhage (sICH) has been well studied, the prognostic impact of asymptomatic intracranial hemorrhage (aICH) after EVT is less certain ...
Shihai Yang +22 more
wiley +1 more source
Fuzzy Adaptive-Sampling Block Compressed Sensing for Wireless Multimedia Sensor Networks
The transmission of high-volume multimedia content (e.g., images) is challenging for a resource-constrained wireless multimedia sensor network (WMSN) due to energy consumption requirements.
Sovannarith Heng +4 more
doaj +1 more source
A Compressed Sampling and Dictionary Learning Framework for WDM-Based Distributed Fiber Sensing
We propose a compressed sampling and dictionary learning framework for fiber-optic sensing using wavelength-tunable lasers. A redundant dictionary is generated from a model for the reflected sensor signal. Imperfect prior knowledge is considered in terms
Weiss, Christian, Zoubir, Abdelhak M.
core +1 more source

