Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: SUMMARY The method of multisplitting, implemented as a restricted additive Schwarz type algorithm, is extended for the solution of regularized least squares problems. The presented non-stationary version of the algorithm uses dynamic updating of the ights applied to the subdomains in reconstituting the global solution. Standard convergence results follow from extensive prior literature on linear multisplitting schemes. Additional convergence results on nonstationary iterations yield convergence conditions for the presented nonstationary multisplitting algorithm. The global iteration uses repeated solves of local problems with changing right hand sides but a xed system matrix. These problems are solved
['Rosemary A. Renaut', 'Youzuo Lin', 'Hongbin Guo']
I am writing a research paper on a idea Multisplitting for Regularized Least Squares with Krylov Subspace Recycling
[{"from": "human", "value": "I am writing a research paper on a idea Multisplitting for Regularized Least Squares with Krylov Subspace Recycling"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: SUMMARY The method of multisplitting, implemented as a restricted additive Schwarz type algorithm, is extended for the solution of regularized least squares problems. The presented non-stationary version of the algorithm uses dynamic updating of the ights applied to the subdomains in reconstituting the global solution. Standard convergence results follow from extensive prior literature on linear multisplitting schemes. Additional convergence results on nonstationary iterations yield convergence conditions for the presented nonstationary multisplitting algorithm. The global iteration uses repeated solves of local problems with changing right hand sides but a xed system matrix. These problems are solved"}]