regularization method_method成员_method记忆法

针对基本解法在求解反问题时的病态特性，将截断奇异值分解（TSVD）、Tikhonov正则化方法应用于所得病态系统方程的求解，采用L曲线法和GCV方法确定其正则参数，并比较了4种组合方法求解的精确性和稳定性。regularization method数值算例表明，TSVD方法、Tikhonov正则化方法结合L曲线法和GCV法可有效地处理反问题中的病态特性。regularization method

In order to resolve ill-conditioned problems existing in the regularization M FS for the 2D boundary conditions identification potential problems ,suitable regularization methods are nee‐ded .The truncated singular value decomposition (TSVD )method and Tikhonov regularization method are used to solve linear systems with a large number of conditions respectively .The L-curve and generalized cross validation (GCV ) methods are employed to determine the optimal reg‐ularization parameters .Furthermore ,the accuracy and robustness of regularization solution for four combined methods are investigated .Numerical results show that TSVD method and Tik‐honov method can effectively solve the ill posed system caused by inverse problems .Through ap‐plying to L-curve method and GCV method ,continuous regularization parameter for Tikhonov method can be confirmed reasonably .

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