Results 131 to 140 of about 2,960,959 (361)

Frequency Selective Compressed Sensing [PDF]

arXiv, 2015
In this paper the authors describe the problem of acquisition of interfered signals and formulate a filtering problem. A frequency-selective compressed sensing technique is proposed as a solution to this problem. Signal acquisition is critical in facilitating frequency-selective compressed sensing.
arxiv  

An Ontology‐Augmented Digital Twin for Fiber‐Reinforced Polymer Structures at the Example of Wind Turbine Rotor Blades

Advanced Engineering Materials, EarlyView.
A methodology for establishing an ontology‐augmented structural digital twin for fiber‐reinforced polymer structures dedicated to individual lifetime prediction, in this case, a wind turbine rotor blade, is introduced. The methodology resembles the manufacturing as well as the operation of the structure.
Marc Luger, Alexander Seidel, Ursula Pähler, Sebastian Schröck, Peter Hofmann, Sebastian Kölbl, Klaus Drechsler   +6 more
wiley   +1 more source

Compressed Sensing With Prior Information: Strategies, Geometry, and Bounds

IEEE Transactions on Information Theory, 2017
We address the problem of compressed sensing (CS) with prior information: reconstruct a target CS signal with the aid of a similar signal that is known beforehand, our prior information. We integrate the additional knowledge of the similar signal into CS
J. Mota, N. Deligiannis, M. Rodrigues
semanticscholar   +1 more source

Determining the Necessity of Post‐Processing Heat Treatment for the 316L Stainless Steel Manufactured by Laser Powder Bed Fusion through Evaluation of Mechanical and Corrosion Properties

Advanced Engineering Materials, EarlyView.
This article examines the effect of postprocessing heat treatment on 316L stainless steel (SS316L) produced via laser powder bed fusion (LPBF). Heat treatment slightly affects property anisotropy, reduces strength, and enhances elongation. However, it increases corrosion susceptibility due to nanoscale precipitations, though overall corrosion ...
Baibhav Karan, Malar Vadani, Prashanth Muralishankar, Kiomars Moheimani, Ayan Bhowmik, Mingxing Zhang   +5 more
wiley   +1 more source

Quantum Annealing Based Binary Compressive Sensing with Matrix Uncertainty [PDF]

arXiv, 2019
Compressive sensing is a novel approach that linearly samples sparse or compressible signals at a rate much below the Nyquist-Shannon sampling rate and outperforms traditional signal processing techniques in acquiring and reconstructing such signals. Compressive sensing with matrix uncertainty is an extension of the standard compressive sensing problem
arxiv  

Restricted Structural Random Matrix for Compressive Sensing [PDF]

arXiv, 2020
Compressive sensing (CS) is well-known for its unique functionalities of sensing, compressing, and security (i.e. CS measurements are equally important). However, there is a tradeoff. Improving sensing and compressing efficiency with prior signal information tends to favor particular measurements, thus decrease the security.
arxiv  

Semantic Orchestration and Exploitation of Material Data: A Dataspace Solution Demonstrated on Steel and Copper Applications

Advanced Engineering Materials, EarlyView.
This article introduces the Dataspace Management System (DSMS), a methodological framework realized in software, designed as a technology stack to power dataspaces with a focus on advanced knowledge management in materials science and manufacturing. DSMS leverages heterogeneous data through semantic integration, linkage, and visualization, aligned with
Yoav Nahshon, Lukas Morand, Matthias Büschelberger, Dirk Helm, Kiran Kumaraswamy, Paul Zierep, Matthias Weber, Pablo de Andrés   +7 more
wiley   +1 more source

A New Compressed Data Acquisition Method for Power System Based on Chaotic Compressive Measurement

Sensors
The digitalization level of the new power system driven by “dual carbon” is increasing, leading to a growth in the amount of data that need to be acquired. This has intensified the contradiction between data volume and acquisition capacity. Therefore, it
Shan Yang, Zhirong Gao, Jingbo Guo
doaj   +1 more source

BREAKING THE COHERENCE BARRIER: A NEW THEORY FOR COMPRESSED SENSING

Forum of Mathematics, Sigma, 2017
This paper presents a framework for compressed sensing that bridges a gap between existing theory and the current use of compressed sensing in many real-world applications.
BEN ADCOCK, ANDERS C. HANSEN, CLARICE POON, BOGDAN ROMAN   +3 more
doaj   +1 more source

CMCS‐net: image compressed sensing with convolutional measurement via DCNN

IET Image Processing, 2020
Recently, deep learning methods have made a remarkable improvement in compressed sensing image recovery stage. In the compressed measurement stage, the existing methods measured by block by block owing to a huge measurement dictionary for the whole ...
Yahong Xie, Hailin Wang, Jianjun Wang
doaj   +1 more source