Sum of outer products dictionary learning for inverse problems

Author(s):  
Saiprasad Ravishankar ◽  
Raj Rao Nadakuditi ◽  
Jeffrey A. Fessler
IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 37039-37049 ◽  
Author(s):  
John Lewis D. ◽  
Vanika Singhal ◽  
Angshul Majumdar

2017 ◽  
Vol 3 (4) ◽  
pp. 694-709 ◽  
Author(s):  
Saiprasad Ravishankar ◽  
Raj Rao Nadakuditi ◽  
Jeffrey A. Fessler

2021 ◽  
Author(s):  
Naomi Schneider ◽  
Volker Michel

<p><span>In the light of significant challenges like the climate change, the visualization of the gravitational potential remains a priority in geodesy. A decade ago, the Geomathematics Group Siegen proposed alternative representations </span><span>for</span><span> such problems. </span></p><p><span>The </span><span>respective</span><span> methods are based on matching pursuits: </span><span>hence,</span><span> they build a representation in a so-called best basis. However, they include additional aspects which occur, for instance, when the downward continuation of the gravitational potential is approximated.</span></p><p><span>In this talk, we summarize </span><span>the different developmental stages from 2011 up to now </span><span>which started with a basic implementation and then included aspects of orthogonality, weakness and dictionary learning, respectively. Further, we </span><span>give an outlook on ou</span><span>r</span><span> next steps </span><span>with these methods</span><span>. For the current status-quo, we show numerical results </span><span>with respect to</span><span> the downward continuation of the gravitational potential.</span></p>


Author(s):  
S.I. Kabanikhin ◽  
◽  
O.I. Krivorotko ◽  
D.V. Ermolenko ◽  
V.N. Kashtanova ◽  
...  
Keyword(s):  

Author(s):  
S.I. Kabanikhin ◽  
O.I. Krivorotko ◽  
D.V. Ermolenko ◽  
V.N. Kashtanova ◽  
V.A. Latyshenko
Keyword(s):  

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