A multilevel augmentation method for solving ill-posed operator equations

We introduce a multilevel augmentation method for solving ill-posed operator equations by making use of the multiscale structure of the matrix representation of the operator. The method leads to fast solutions of the discrete regularization methods for the equations. Choices for a priori and a posteriori regularization parameters are proposed. An optimal convergence order for the method with the choices of parameters is established. Numerical results are presented to illustrate the accuracy and efficiency of the method.

[1]  C. W. Groetsch,et al.  The theory of Tikhonov regularization for Fredholm equations of the first kind , 1984 .

[2]  Robert Plato,et al.  On the regularization of projection methods for solving III-posed problems , 1990 .

[3]  R. Coifman,et al.  Fast wavelet transforms and numerical algorithms I , 1991 .

[4]  Wolfgang Dahmen,et al.  Wavelet approximation methods for pseudodifferential equations II: Matrix compression and fast solution , 1993, Adv. Comput. Math..

[5]  C. Micchelli,et al.  Using the Matrix Refinement Equation for the Construction of Wavelets on Invariant Sets , 1994 .

[6]  R. Plato,et al.  On pseudo-optimal parameter choices and stopping rules for regularization methods in Banach spaces , 1996 .

[7]  R. Plato On the discrepancy principle for iterative and parametric methods to solve linear ill-posed equations , 1996 .

[8]  P. Maass,et al.  Wavelet-Galerkin methods for ill-posed problems , 1996 .

[9]  Andreas Rieder,et al.  A wavelet multilevel method for ill-posed problems stabilized by Tikhonov regularization , 1997 .

[10]  Robert Plato The Galerkin scheme for Lavrentiev’sm-times iterated method to solve linear accretive Volterra integral equations of the first kind , 1997 .

[11]  Yuesheng Xu,et al.  The Petrov–Galerkin method for second kind integral equations II: multiwavelet schemes , 1997, Adv. Comput. Math..

[12]  Yuesheng Xu,et al.  Reconstruction and Decomposition Algorithms for Biorthogonal Multiwavelets , 1997, Multidimens. Syst. Signal Process..

[13]  Charles A. Micchelli,et al.  Wavelet Galerkin methods for second-kind integral equations , 1997 .

[14]  Jin Qi-nian,et al.  On an a posteriori parameter choice strategy for Tikhonov regularization of nonlinear ill-posed problems , 1999 .

[15]  Martin Hanke,et al.  Two-level preconditioners for regularized inverse problems I: Theory , 1999, Numerische Mathematik.

[16]  Yuesheng Xu,et al.  A construction of interpolating wavelets on invariant sets , 1999, Math. Comput..

[17]  Kyle L. Riley Two-level preconditioners for regularized ill-posed problems , 1999 .

[18]  Ronny Ramlau,et al.  An adaptive discretization for Tikhonov-Phillips regularization with a posteriori parameter selection , 2001, Numerische Mathematik.

[19]  Charles A. Micchelli,et al.  A Multilevel Method for Solving Operator Equations , 2001 .

[20]  B. Kaltenbacher On the regularizing properties of a full multigrid method for ill-posed problems , 2001 .

[21]  Yuesheng Xu,et al.  Fast Collocation Methods for Second Kind Integral Equations , 2002, SIAM J. Numer. Anal..

[22]  Yuesheng Xu,et al.  Discrete Wavelet Petrov–Galerkin Methods , 2002, Adv. Comput. Math..

[23]  Hongqi Yang,et al.  A Posteriori Parameter Choice Strategy for Nonlinear Monotone Operator Equations , 2002 .

[24]  Reinhold Schneider,et al.  Self–regularization by projection for noisy pseudodifferential equations of negative order , 2003, Numerische Mathematik.

[25]  P. Mathé,et al.  Discretization strategy for linear ill-posed problems in variable Hilbert scales , 2003 .

[26]  S G Solodky On a quasi-optimal regularized projection method for solving operator equations of the first kind , 2005 .

[27]  陈仲英,et al.  MULTILEVEL AUGMENTATION METHODS FOR SOLVING OPERATOR EQUATIONS , 2005 .