Results 81 to 90 of about 279,028 (324)

Gradient-Based Methods for Sparse Recovery [PDF]

SIAM Journal on Imaging Sciences, 2011
16 pages, submitted to SIAM Journal on Imaging ...
Hager, William, Phan, Dzung, Zhang, Hongchao   +2 more
openaire   +2 more sources

Distributed Multi-View Sparse Vector Recovery

IEEE Transactions on Signal Processing, 2023
In this paper, we consider a multi-view compressed sensing problem, where each sensor can only obtain a partial view of the global sparse vector. Here the partial view means that some arbitrary and unknown indices of the global vector are unobservable to that sensor and do not contribute to the measurement outputs.
Zhuojun Tian, Zhaoyang Zhang, Lajos Hanzo   +2 more
openaire   +3 more sources

Spectrally Tunable 2D Material‐Based Infrared Photodetectors for Intelligent Optoelectronics

Advanced Functional Materials, EarlyView.
Intelligent optoelectronics through spectral engineering of 2D material‐based infrared photodetectors. Abstract The evolution of intelligent optoelectronic systems is driven by artificial intelligence (AI). However, their practical realization hinges on the ability to dynamically capture and process optical signals across a broad infrared (IR) spectrum.
Junheon Ha, Yingshan Ma, Yong Nam An, Sung‐Un An, Hyeon Hak Jung, Suvi‐Tuuli Varjamo, Jiwon Yoo, Junho Min, Hanvit Kim, Faisal Ahmed, Sang Hoon Chae, Young Min Song, Weiwei Cai, Tawfique Hasan, Zhipei Sun, Dong‐Ho Kang, Hyeon‐Jin Shin, Yunyun Dai, Hoon Hahn Yoon   +18 more
wiley   +1 more source

Space alternating variational estimation based sparse Bayesian learning for complex‐value sparse signal recovery using adaptive Laplace priors

IET Signal Processing, 2023
Due to its self‐regularising nature and its ability to quantify uncertainty, the Bayesian approach has achieved excellent recovery performance across a wide range of sparse signal recovery applications.
Zonglong Bai, Liming Shi, Jinwei Sun, Mads Græsbøll Christensen   +3 more
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  

Exact sparse recovery with L0 projections [PDF]

Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining, 2013
Many applications concern sparse signals, for example, detecting anomalies from the differences between consecutive images taken by surveillance cameras. This paper focuses on the problem of recovering a K-sparse signal x in N dimensions. In the mainstream framework of compressed sensing (CS), the vector x is recovered from M non-adaptive linear ...
Li, Ping, Zhang, Cun-Hui
openaire   +2 more sources

Interconnected Porous Hydrogels with Tunable Anisotropy Through Aqueous Emulsion Bioprinting

Advanced Functional Materials, EarlyView.
A 3D bioprintable microporous bioink is developed using an aqueous two‐phase system (ATPS) composed of extracellular matrix (ECM) mimetic biopolymers. The ATPS bioink enables the fabrication of interconnected porous architectures with up to 70% porosity, supporting long‐term cell viability and 3D cell alignment, enabling a simultaneous generation of ...
Hugo Edgar‐Vilar, Francisca P. Correia, Inês M. Freitas, Vítor M. Gaspar, João F. Mano   +4 more
wiley   +1 more source

Adaptive Sensing for Sparse Signal Recovery [PDF]

2009 IEEE 13th Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009
The theory of compressed sensing shows that sparse signals in high-dimensional spaces can be recovered from a relatively small number of samples in the form of random projections. However, in severely resource-constrained settings even CS techniques may fail, and thus, a less aggressive goal of partial signal recovery is reasonable.
Haupt, J., Nowak, R., Castro, R.M.
openaire   +1 more source

Predicting Atomic Charges in MOFs by Topological Charge Equilibration

Advanced Functional Materials, EarlyView.
An atomic charge prediction method is presented that is able to accurately reproduce ab‐initio‐derived reference charges for a large number of metal–organic frameworks. Based on a topological charge equilibration scheme, static charges that fulfill overall neutrality are quickly generated.
Babak Farhadi Jahromi, Sumukh Shankar Sharadaprasad, Rochus Schmid   +2 more
wiley   +1 more source

An Ultrafast Self‐Gelling Versatile Hydrogel for Rapid Infected Burn Wound Repair in Military Medicine

Advanced Functional Materials, EarlyView.
A self‐gelling PG@PAC (POD/Gel‐CDH@PA/CHX) powder is developed for infected burn care in austere settings. Upon contact with wound exudate, it instantly forms an adhesive hydrogel, providing simultaneous hemostasis, broad‐spectrum antibacterial activity, reactive oxygen species scavenging, and immunomodulation. In a murine model of S.
Liping Zhang, Zhangrui Wu, Xiansheng Zhao, Geng Wang, Quyang Yang, Minxia zhang, Xiaowei Wang, Xiujun Cheng, Changyue Wu, Dan Wu, Yutian Yang, Canbin Dong, Tao Zhang, Weiqiang Tan, Ningwen Zhu   +14 more
wiley   +1 more source