scholarly journals Observational evidence for polar spots

1996 ◽  
Vol 176 ◽  
pp. 289-298 ◽  
Author(s):  
Klaus G. Strassmeier
Keyword(s):  
Image Reconstruction ◽  
Observational Evidence ◽  
Doppler Imaging ◽  
Stellar Rotation ◽  
Rotation Pole ◽  
Ill Posed

“Are results from ill-posed problems, like Doppler-imaging, conclusive at all?” and “Could polar spots be simple image-reconstruction artifacts?” are often asked questions. Although I can not definitively answer them, I will present observational evidence for the existence of cool starspots at or very near a stellar rotation pole.

Patch-based sparse reconstruction for electrical impedance tomography

Sensor Review ◽  
2017 ◽  
Vol 37 (3) ◽  
pp. 257-269 ◽  
Author(s):  
Qi Wang ◽  
Pengcheng Zhang ◽  
Jianming Wang ◽  
Qingliang Chen ◽  
Zhijie Lian ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Sparse Representation ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Inverse Operator ◽  
Reconstruction Algorithm ◽  
Impedance Tomography ◽  
Content Type ◽  
Ill Posed ◽  
High Level

Purpose Electrical impedance tomography (EIT) is a technique for reconstructing the conductivity distribution by injecting currents at the boundary of a subject and measuring the resulting changes in voltage. Image reconstruction for EIT is a nonlinear problem. A generalized inverse operator is usually ill-posed and ill-conditioned. Therefore, the solutions for EIT are not unique and highly sensitive to the measurement noise. Design/methodology/approach This paper develops a novel image reconstruction algorithm for EIT based on patch-based sparse representation. The sparsifying dictionary optimization and image reconstruction are performed alternately. Two patch-based sparsity, namely, square-patch sparsity and column-patch sparsity, are discussed and compared with the global sparsity. Findings Both simulation and experimental results indicate that the patch based sparsity method can improve the quality of image reconstruction and tolerate a relatively high level of noise in the measured voltages. Originality/value EIT image is reconstructed based on patch-based sparse representation. Square-patch sparsity and column-patch sparsity are proposed and compared. Sparse dictionary optimization and image reconstruction are performed alternately. The new method tolerates a relatively high level of noise in measured voltages.

scholarly journals Mass Loss and Stellar Rotation

2004 ◽  
Vol 215 ◽  
pp. 479-490 ◽  
Author(s):  
Henny J.G.L.M. Lamers
Keyword(s):  
Mass Loss ◽  
Mass Flux ◽  
Equatorial Plane ◽  
Observational Evidence ◽  
Agb Stars ◽  
Stellar Rotation ◽  
Cool Stars ◽  
Spherical Mass

The observational evidence for non-spherical winds of rapidly rotating hot and cool stars is presented. Models to explain equatorially enhanced winds of AGB stars and of hot B[e]-supergiants are discussed. We distinguish between models with a disk due to an increased equatorial mass flux and those with a disk due to spherical mass loss with a wind flowing towards the equatorial plane.

scholarly journals High Resolution Imaging of Compact Radio Sources by Gridding with Regularization

1998 ◽  
Vol 164 ◽  
pp. 411-412 ◽  
Author(s):  
S. F. Likhachev ◽  
R. M. Hjellming
Keyword(s):  
High Resolution ◽  
Image Reconstruction ◽  
Radio Source ◽  
Radio Sources ◽  
High Resolution Imaging ◽  
Traditional Methods ◽  
Compact Radio Source ◽  
Ill Posed ◽  
Resolution Imaging

AbstractThe problem of VLBI image reconstruction is a classical example of an ill-posed problem. A new procedure of gridding with regularization has been developed. This procedure was used in traditional methods (CLEAN, Hybrid) to improve the quality of compact radio source images. A few sources (GRO J1655–40, RY Scuti and Cyg X-1), observed with the VLA and VLBA, were processed with this procedure.

scholarly journals Minimal Linear Networks for Magnetic Resonance Image Reconstruction

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Gilad Liberman ◽  
Benedikt A. Poser
Keyword(s):  
Deep Learning ◽  
Magnetic Resonance ◽  
Image Reconstruction ◽  
Simulated Data ◽  
Linear Networks ◽  
Learning Framework ◽  
Scan Time ◽  
Learning Techniques ◽  
Ill Posed ◽  
Magnetic Resonance Imaging Mri

AbstractModern sequences for Magnetic Resonance Imaging (MRI) trade off scan time with computational challenges, resulting in ill-posed inverse problems and the requirement to account for more elaborated signal models. Various deep learning techniques have shown potential for image reconstruction from reduced data, outperforming compressed sensing, dictionary learning and other advanced techniques based on regularization, by characterization of the image manifold. In this work we suggest a framework for reducing a “neural” network to the bare minimum required by the MR physics, reducing the network depth and removing all non-linearities. The networks performed well both on benchmark simulated data and on arterial spin labeling perfusion imaging, showing clear images while preserving sensitivity to the minute signal changes. The results indicate that the deep learning framework plays a major role in MR image reconstruction, and suggest a concrete approach for probing into the contribution of additional elements.

A NOVEL TWO-STAGE GENETIC ALGORITHM FOR IMAGE RECONSTRUCTION OF ELECTRICAL RESISTANCE TOMOGRAPHY

2010 ◽  
Vol 01 (04) ◽  
pp. 523-542
Author(s):  
SANAZ ASGARIFAR ◽  
JAVAD FROUNCHI ◽  
MOHAMMAD HOSSIEN ZARIFI ◽  
AMIN MAHDIZADEH
Keyword(s):  
Genetic Algorithm ◽  
Image Reconstruction ◽  
Electrical Resistance ◽  
Process Time ◽  
Initial Population ◽  
Two Stage ◽  
Electrical Resistance Tomography ◽  
Random Group ◽  
Ill Posed ◽  
Resistivity Inversion

In this paper, we present a combined GA-ERT method based on two-stage genetic algorithm for image reconstruction in electrical resistance tomography (ERT). Image reconstruction in ERT is an ill-posed inverse problem and we have replaced the reverse solver by a two-stage optimization algorithm. The first stage of GA-ERT is reach to an approximate shape and location of the object. Also in this stage, we proposed a new electrode arrangement for ERT forward solver to reduce the process time of the forward problem. In the second stage, the GA employs result of the first stage as an initial population instead of a random group. Therefore with the local zoom, the GA can be employed to obtain the shape and location of the object more precisely. Experimental results of numerically solved ERT by the GA are also presented and compared to those obtained by other more established inversion methods such as modified Newton–Raphson (mNR) and RES2DINV program which is a standard 2-D resistivity inversion program. Results show that the proposed method can efficiently improve the ill-posed condition of ERT image reconstruction problem and can superiorly enhance the quality of ERT images.

Error minimizing relaxation strategies in Landweber and Kaczmarz type iterations

2017 ◽  
Vol 25 (1) ◽  
Author(s):  
Touraj Nikazad ◽  
Mokhtar Abbasi ◽  
Tommy Elfving
Keyword(s):  
Image Reconstruction ◽  
Linear Systems ◽  
Operator Theory ◽  
Convex Constraints ◽  
Advantages And Disadvantages ◽  
Exact Data ◽  
Convergence Results ◽  
Ill Posed ◽  
Image Reconstruction From Projections

AbstractWe study error minimizing relaxation (EMR) strategies for use in Landweber and Kaczmarz type iterations applied to linear systems with or without convex constraints. Convergence results based on operator theory are given, assuming exact data. The advantages and disadvantages of these relaxation strategies on a noisy and ill-posed problem are illustrated using examples taken from the field of image reconstruction from projections. We also consider combining EMR with penalization.

scholarly journals Stellar magnetic activity and their influence on the habitability of exoplanets

2014 ◽  
Vol 10 (S305) ◽  
pp. 333-339
Author(s):  
T. Lüftinger ◽  
M. Güdel ◽  
C. Johnstone
Keyword(s):  
Magnetic Fields ◽  
International Research ◽  
Planetary Systems ◽  
Magnetic Activity ◽  
Doppler Imaging ◽  
Research Network ◽  
Stellar Rotation ◽  
Theoretical Understanding ◽  
Points Of View ◽  
Stellar Magnetic Fields

AbstractStellar magnetism, explorable via polarimetry, is a crucial driver of activity, ionization, photodissociation, chemistry and winds in stellar environments. Thus it has an important impact on the atmospheres and magnetospheres of surrounding planets. Modeling of stellar magnetic fields and their winds is extremely challenging, both from the observational and the theoretical points of view, and only recent ground breaking advances in observational instrumentation - as were discussed during this Symposium - and a deeper theoretical understanding of magnetohydrodynamic processes in stars enable us to model stellar magnetic fields and winds and the resulting influence on surrounding planets in more and more detail. We have initiated a national and international research network (NFN): ‘Pathways to Habitability - From Disks to Active Stars, Planets to Life’, to address questions on the formation and habitability of environments in young, active stellar/planetary systems. In this contribution we discuss the work we are carrying out within this project and focus on how stellar magnetic fields, their winds and the relation to stellar rotation can be assessed observationally with relevant techniques such as Zeeman Doppler Imaging (ZDI), field extrapolation and wind simulations.

Zeeman Doppler Imaging of Stars with the AAT

1996 ◽  
Vol 13 (2) ◽  
pp. 150-155 ◽  
Author(s):  
Brad Carter ◽  
Steve Brown ◽  
Jean-François Donati ◽  
David Rees ◽  
Meir Semel
Keyword(s):  
Magnetic Field ◽  
Zeeman Effect ◽  
Rotation Period ◽  
Doppler Imaging ◽  
Time Interval ◽  
Stellar Rotation ◽  
Echelle Spectrograph ◽  
Active Stars ◽  
Rotating Star ◽  
The Many

AbstractZeeman Doppler Imaging (ZDI) is a recent technique for measuring magnetic fields on rapidly rotating, active stars. ZDI employs spectropolarimetry taken at different rotational phases to derive information on the magnetic field distribution over the stellar surface. The Zeeman effect is used to identify the presence of a magnetic field, and variations in Doppler wavelength shifts across the rapidly rotating star allow fields to be resolved on different parts of the visible disk. Analysis of the spectra can be used to produce both thermal and surface magnetic images. ZDI requires very high S/N spectra to be acquired within a time interval short compared to the stellar rotation period. As a result, a large-aperture telescope is needed. Since an initial successful test in 1989, the 3·9 m Anglo-Australian Telescope has been used to obtain ZDI spectra of active stars of different evolutionary stages. The observations have concentrated on the K subgiant in the RSCVn system HR 1099 to monitor changes on this bright and active star. With the advent in 1991 of ZDI spectropolarimetry with the AAT échelle spectrograph, it has become possible to co-add the polarisation signature from the many magnetically sensitive lines recorded simultaneously. As a result, stellar magnetic field detections of unprecedented quality have been obtained. The aims of this paper are to briefly outline the principles of ZDI, describe the instrumental setup at the AAT and present some preliminary results from recent observations.

Preliminary Results of Integrating Tikhonov’s Regularization in Forward-Backward Time-Stepping Technique for Object Detection

2016 ◽  
Vol 833 ◽  
pp. 170-175 ◽  
Author(s):  
Andrew Sia Chew Chie ◽  
Kismet Anak Hong Ping ◽  
Yong Guang ◽  
Ng Shi Wei ◽  
Nordiana Rajaee
Keyword(s):  
Image Reconstruction ◽  
Inverse Scattering ◽  
Time Domain ◽  
Regularization Method ◽  
Scattering Problem ◽  
Inverse Scattering Problem ◽  
Time Stepping ◽  
Ill Posed ◽  
Tikhonov’S Regularization

The inverse scattering in time domain known as Forward-Backward Time-Stepping (FBTS) technique is applied to determine the sizes, shape and location of the embedded objects. Tikhonov’s regularization method has been proposed in order to improve or solve the ill-posed of FBTS inverse scattering problem. The reconstructed results showed that FBTS technique can detect the presence of embedded objects. The reconstructed results of FBTS technique utilizing with the Tikhonov’s regularization method shown better results than the results only applied FBTS technique. Tikhonov’s regularization combined with FBTS technique to improve the quality of image reconstruction.

scholarly journals Image Reconstruction Based on Homotopy Perturbation Inversion Method for Electrical Impedance Tomography

2013 ◽  
Vol 2013 ◽  
pp. 1-11 ◽  
Author(s):  
Jing Wang ◽  
Bo Han
Keyword(s):  
Image Reconstruction ◽  
Electrical Impedance Tomography ◽  
Electrical Impedance ◽  
Perturbation Technique ◽  
Inversion Method ◽  
Impedance Tomography ◽  
Data Noise ◽  
Homotopy Perturbation ◽  
Ill Posed ◽  
Homotopy Perturbation Technique

The image reconstruction for electrical impedance tomography (EIT) mathematically is a typed nonlinear ill-posed inverse problem. In this paper, a novel iteration regularization scheme based on the homotopy perturbation technique, namely, homotopy perturbation inversion method, is applied to investigate the EIT image reconstruction problem. To verify the feasibility and effectiveness, simulations of image reconstruction have been performed in terms of considering different locations, sizes, and numbers of the inclusions, as well as robustness to data noise. Numerical results indicate that this method can overcome the numerical instability and is robust to data noise in the EIT image reconstruction. Moreover, compared with the classical Landweber iteration method, our approach improves the convergence rate. The results are promising.

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