scholarly journals A hybrid multilevel-active set method for large box-constrained linear discrete ill-posed problems

CALCOLO ◽  
2010 ◽  
Vol 48 (1) ◽  
pp. 89-105 ◽  
Author(s):  
S. Morigi ◽  
R. Plemmons ◽  
L. Reichel ◽  
F. Sgallari
Keyword(s):  
Active Set ◽  
Active Set Method ◽  
Ill Posed

Regularizing active set method for nonnegatively constrained ill-posed multichannel image restoration problem

2009 ◽  
Vol 48 (7) ◽  
pp. 1389 ◽  
Author(s):  
Yanfei Wang ◽  
Jingjie Cao ◽  
Yaxiang Yuan ◽  
Changchun Yang ◽  
Naihua Xiu
Keyword(s):  
Image Restoration ◽  
Active Set ◽  
Active Set Method ◽  
Ill Posed ◽  
Restoration Problem

scholarly journals A Distributed Active Set Method for Model Predictive Control

2021 ◽  
Vol 54 (3) ◽  
pp. 263-268
Author(s):  
Gösta Stomberg ◽  
Alexander Engelmann ◽  
Timm Faulwasser
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Active Set ◽  
Active Set Method

A conjugate gradient least square based method for sound field control

2021 ◽  
Vol 263 (5) ◽  
pp. 1029-1040
Author(s):  
Pierangelo Libianchi ◽  
Finn T. Agerkvist ◽  
Elena Shabalina
Keyword(s):  
Conjugate Gradient ◽  
Regularization Parameter ◽  
Sound Field ◽  
Least Square ◽  
Active Set ◽  
Noise Sources ◽  
Field Control ◽  
Ill Posed ◽  
The Right ◽  
Number Of Iterations

In sound field control, a set of control sources is used to match the pressure field generated by noise sources but with opposite phase to reduce the total sound pressure level in a defined area commonly referred to as dark zone. This is usually an ill-posed problem. The approach presented here employs a subspace iterative method where the number of iterations acts as the regularization parameter and controls unwanted side radiation, i.e. side lobes. More iterations lead to less regularization and more side lobes. The number of iterations is controlled by problem-specific stopping criteria. Simulations show the increase of lobing with increased number of iterations. The solutions are analysed through projections on the basis provided by the source strength modes corresponding to the right singular vector of the transfer function matrix. These projections show how higher order pressure modes (left singular vectors) become dominant with larger number of iterations. Furthermore, an active-set type method provides the constraints on the amplitude of the solution which is not possible with the conjugate gradient least square algorithm alone.

Continuous GRASP with a local active-set method for bound-constrained global optimization

2009 ◽  
Vol 48 (2) ◽  
pp. 289-310 ◽  
Author(s):  
Ernesto G. Birgin ◽  
Erico M. Gozzi ◽  
Mauricio G. C. Resende ◽  
Ricardo M. A. Silva
Keyword(s):  
Global Optimization ◽  
Constrained Global Optimization ◽  
Active Set ◽  
Active Set Method

scholarly journals Projected Preconditioning within a Block-Sparse Active-Set Method for MPC

2018 ◽  
Vol 51 (20) ◽  
pp. 28-34
Author(s):  
Rien Quirynen ◽  
Andrew Knyazev ◽  
Stefano Di Cairano
Keyword(s):  
Active Set ◽  
Active Set Method
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