Results 31 to 40 of about 7,447 (293)

Variational Bayesian algorithm for distributed compressive sensing [PDF]

2015 IEEE International Conference on Communications (ICC), 2015
Distributed compressive sensing (DCS) concerns the reconstruction of multiple sensor signals with reduced numbers of measurements, which exploits both intra- and inter-signal correlations. In this paper, we propose a novel Bayesian DCS algorithm based on variational Bayesian inference.
Chen, W, Wassell, IJ
openaire   +2 more sources

Distributed Compressed Hyperspectral Sensing Imaging Incorporated Spectral Unmixing and Learning

Journal of Spectroscopy, 2022
Compressed hyperspectral imaging is a powerful technique for satellite-borne and airborne sensors that can effectively shift the complex computational burden from the resource-constrained encoding side to a presumably more capable base-station decoder ...
Hua Xiao, Zhongliang Wang, Xueying Cui, Liping Wang, Hongsheng Yang, Yingbiao Jia   +5 more
doaj   +1 more source

Energy-Efficient Distributed Compressed Sensing Data Aggregation for Cluster-Based Underwater Acoustic Sensor Networks

International Journal of Distributed Sensor Networks, 2016
Energy-efficient data aggregation is important for underwater acoustic sensor networks due to its energy constrained character. In this paper, we propose a kind of energy-efficient data aggregation scheme to reduce communication cost and to prolong ...
Deqing Wang, Ru Xu, Xiaoyi Hu, Wei Su
doaj   +1 more source

Distributed compressed sensing for sensor networks with packet erasures [PDF]

2014 IEEE Global Communications Conference, 2014
We study two approaches to distributed compressed sensing for in-network data compression and signal reconstruction at a sink in a wireless sensor network where sensors are placed on a straight line. Communication to the sink is considered to be bandwidth-constrained due to the large number of devices.
Christopher Lindberg, Alexandre Graell i Amat, Henk Wymeersch   +2 more
openaire   +3 more sources

Distributed Compressed Sensing for Static and Time-Varying Networks [PDF]

IEEE Transactions on Signal Processing, 2014
We consider the problem of in-network compressed sensing from distributed measurements. Every agent has a set of measurements of a signal $x$, and the objective is for the agents to recover $x$ from their collective measurements using only communication with neighbors in the network.
Idit Keidar, Yonina C. Eldar, Stacy Patterson   +2 more
openaire   +2 more sources

Distributed Compressed Video Sensing in Camera Sensor Networks

International Journal of Distributed Sensor Networks, 2012
With the booming of video devices ranging from low-power visual sensors to mobile phones, the video sequences captured by these simple devices must be compressed easily and reconstructed by relatively more powerful servers. In such scenarios, distributed
Yu Liu, Xuqi Zhu, Lin Zhang, Sung Ho Cho
doaj   +1 more source

Generalized Distributed Compressive Sensing

, 2012
Distributed Compressive Sensing (DCS) improves the signal recovery performance of multi signal ensembles by exploiting both intra- and inter-signal correlation and sparsity structure. However, the existing DCS was proposed for a very limited ensemble of signals that has single common information \cite{Baron:2009vd}.
Park, Jeonghun, Hwang, Seunggye, Yang, Janghoon, Kim, Dongku   +3 more
openaire   +2 more sources

The effect of foot orthoses on midfoot pain and the volume of bone marrow lesions in the midfoot: a randomized mechanism of action study

Arthritis Care &Research, Accepted Article.
Objective Foot orthoses are thought to improve pain by potentially modifying internal mechanical forces. To test this, we explored whether foot orthoses can modify patterns of bone marrow lesions (BMLs) in people with midfoot pain. Methods Forty‐two people were recruited with midfoot pain and MRI‐confirmed midfoot BMLs.
Jill Halstead, Anne‐Maree Keenan, Philip G. Conaghan, Dennis McGonagle, Anthony C. Redmond   +4 more
wiley   +1 more source

Distributed Compressed Sensing MRI Using Volume Array Coil

International Journal of Distributed Sensor Networks, 2013
The volume array coil in the magnetic resonance imaging (MRI) system is a typical application of the distributed sensor network in the biomedical area.
Zhen Feng, Feng Liu, He Guo, Zhikui Chen, Mingfeng Jiang, Mingjian Hong, Qi Jia   +6 more
doaj   +1 more source

Compressive Learning in Communication Systems: A Neural Network Receiver for Detecting Compressed Signals in OFDM Systems

IEEE Access, 2021
Nowadays, the development of efficient communication system is necessary for future networks. Compressive sensing was proposed as a technique to save storage and energy by compressing signals using simple linear transformations.
Pedro H. C. De Souza, Luciano Leonel Mendes, Marwa Chafii   +2 more
doaj   +1 more source