Results 111 to 120 of about 204,120 (332)
Coprime Interpolation and Compressive Sensing for Future Heterogeneous Network Towards 5G
IEEE Access, 2017 Because of enormous amount of images and videos to be transmitted in 5G, it is quite desirable to do aggressive downsampling in the transmission side.
Na Wu, Qilian Liang
doaj +1 more source
Advanced Engineering Materials, EarlyView.Laser powder‐bed fusion (L‐PBF) can produce dense WE43 magnesium alloy parts, but their mechanical properties are limited by a nonhomogeneous microstructure. This study investigates the effects of varying direct aging (T5) and artificial age‐hardening (T6) conditions on microstructure and strength. Optimized T6 treatment significantly improves strength
Prathviraj Upadhyaya +5 more
wiley +1 more source
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
Advanced Engineering Materials, EarlyView.The share of technical thermoplastics is expected to grow further in the e‐mobility segment. In this study, a detailed temperature‐based tribological characterization of technical thermoplastics is performed. The tribological properties are discussed in terms of the dynamic mechanical properties of polymers at different ambient temperatures. A proof of
Harsha Raghuram +2 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
InformationClassic video compression methods usually suffer from long encode time and requires large memories, making it hard to deploy on edge devices; thus, video compressive sensing, which requires less resources during encoding, is receiving more attention.
Lisha Gao +5 more
doaj +1 more source
IEEE Access, 2016 The broadband spectrum contains significantly more information than what the human eye can detect, with different wavelengths providing unique information about the intrinsic properties of an object.
Edward Li +3 more
doaj +1 more source
The Cognitive Compressive Sensing Problem
, 2014 In the Cognitive Compressive Sensing (CCS) problem, a Cognitive Receiver (CR) seeks to optimize the reward obtained by sensing an underlying $N$ dimensional random vector, by collecting at most $K$ arbitrary projections of it.
Bagheri, Saeed, Scaglione, Anna
core
2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2012 In this paper we present a novel compressed sensing (CS) algorithm for the recovery of compressible, possibly time-varying, signal from a sequence of noisy observations. The newly derived scheme is based on the acclaimed unscented Kalman filter (UKF), and is essentially self reliant in the sense that no peripheral optimization or CS algorithm is ...
Carmi, Avishy Y. +2 more
openaire +3 more sources
Advanced Engineering Materials, EarlyView.Previous studies on additive manufacturing primarily focus on the mechanical properties of as‐printed components. In the present work, researchers explore the potential of employing novel thermomechanical postprocessing techniques to improve the microstructure after printing.
Radim Kocich +3 more
wiley +1 more source