Conventional and Subspace Algorithms for Mobile Source Detection and Radiation Formation

2021 ◽  
Vol 38 (1) ◽  
pp. 135-145
Author(s):  
Sadiya Thazeen ◽  
S Mallikarjunaswamy ◽  
G K Siddesh ◽  
N Sharmila
2021 ◽  
Author(s):  
Adam Augustyniak ◽  
David J. Hanley ◽  
Timothy W. Bretl ◽  
Neil J. Hejmanowski ◽  
David L. Carroll

Proceedings ◽  
2019 ◽  
Vol 33 (1) ◽  
pp. 21
Author(s):  
Fabrizia Guglielmetti ◽  
Eric Villard ◽  
Ed Fomalont

A stable and unique solution to the ill-posed inverse problem in radio synthesis image analysis is sought employing Bayesian probability theory combined with a probabilistic two-component mixture model. The solution of the ill-posed inverse problem is given by inferring the values of model parameters defined to describe completely the physical system arised by the data. The analysed data are calibrated visibilities, Fourier transformed from the ( u , v ) to image planes. Adaptive splines are explored to model the cumbersome background model corrupted by the largely varying dirty beam in the image plane. The de-convolution process of the dirty image from the dirty beam is tackled in probability space. Probability maps in source detection at several resolution values quantify the acquired knowledge on the celestial source distribution from a given state of information. The information available are data constrains, prior knowledge and uncertain information. The novel algorithm has the aim to provide an alternative imaging task for the use of the Atacama Large Millimeter/Submillimeter Array (ALMA) in support of the widely used Common Astronomy Software Applications (CASA) enhancing the capabilities in source detection.


2017 ◽  
Vol 29 (18) ◽  
pp. e4203
Author(s):  
Gunther H. Weber ◽  
Mark S. Bandstra ◽  
Daniel H. Chivers ◽  
Hamdy H. Elgammal ◽  
Valerie Hendrix ◽  
...  

2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
Alkinoos Athanasiou ◽  
Chrysa Lithari ◽  
Konstantina Kalogianni ◽  
Manousos A. Klados ◽  
Panagiotis D. Bamidis

Introduction. Sensorimotor cortex is activated similarly during motor execution and motor imagery. The study of functional connectivity networks (FCNs) aims at successfully modeling the dynamics of information flow between cortical areas.Materials and Methods. Seven healthy subjects performed 4 motor tasks (real foot, imaginary foot, real hand, and imaginary hand movements), while electroencephalography was recorded over the sensorimotor cortex. Event-Related Desynchronization/Synchronization (ERD/ERS) of the mu-rhythm was used to evaluate MI performance. Source detection and FCNs were studied with eConnectome.Results and Discussion. Four subjects produced similar ERD/ERS patterns between motor execution and imagery during both hand and foot tasks, 2 subjects only during hand tasks, and 1 subject only during foot tasks. All subjects showed the expected brain activation in well-performed MI tasks, facilitating cortical source estimation. Preliminary functional connectivity analysis shows formation of networks on the sensorimotor cortex during motor imagery and execution.Conclusions. Cortex activation maps depict sensorimotor cortex activation, while similar functional connectivity networks are formed in the sensorimotor cortex both during actual and imaginary movements. eConnectome is demonstrated as an effective tool for the study of cortex activation and FCN. The implementation of FCN in motor imagery could induce promising advancements in Brain Computer Interfaces.


2014 ◽  
Vol 701-702 ◽  
pp. 492-497
Author(s):  
Teng Yue Ba ◽  
Xi Qiang Guan ◽  
Jian Wu Zhang

In this paper, subspace identification methods are proposed to estimate the linear tire cornering stiffness, which are only based on the road tests data without any prior knowledge. This kind of data-driven method has strong robustness. In order to validate the feasibility and effectiveness of the algorithms, a series of standard road tests are carried out. Comparing with different subspace algorithms used in road tests, it can be concluded that the front tire cornering stiffness can be estimated accurately by the N4SID and CCA methods when the double lane change test data are taken into analysis.


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