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Arnoldi Projection Fractional Tikhonov for Large Scale Ill-Posed Problems 被引量:1
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作者 Wang Zhengsheng Mu Liming +1 位作者 Liu Rongrong Xu Guili 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2018年第3期395-402,共8页
It is well known that Tikhonov regularization in standard form may determine approximate solutions that are too smooth for ill-posed problems,so fractional Tikhonov methods have been introduced to remedy this shortcom... It is well known that Tikhonov regularization in standard form may determine approximate solutions that are too smooth for ill-posed problems,so fractional Tikhonov methods have been introduced to remedy this shortcoming.And Tikhonov regularization for large-scale linear ill-posed problems is commonly implemented by determining apartial Arnoldi decomposition of the given matrix.In this paper,we propose a new method to compute an approximate solution of large scale linear discrete ill-posed problems which applies projection fractional Tikhonov regularization in Krylov subspace via Arnoldi process.The projection fractional Tikhonov regularization combines the fractional matrices and orthogonal projection operators.A suitable value of the regularization parameter is determined by the discrepancy principle.Numerical examples with application to image restoration are carried out to examine that the performance of the method. 展开更多
关键词 ill-posed problems fractional matrix Tikhonov regularization orthogonal projection operator image restoration
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