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Some regularization methods are presented.
This problem demands some regularization method to stabilize the solution.
To overcome such difficulties, some regularization techniques are required [5].
Figure 3 The results for some regularization parameters.
Ill-posed equations need some regularization method (cf. [26]) in order to obtain a stable solution.
Therefore, coping with that impediment helps us improve the use of some regularization methods in real-world applications.
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This makes some regularization-based methods including the feature-enhanced image approach ambiguous in both parameter selection and controlling the sparsity of the recovery.
A common approach to treat these problems is to reformulate these problems into some well-posed problems by some numerical regularization methods.
To deal with this problem; some relaxation (regularization) techniques can be used.
So, the numerical simulation is very difficult and some special regularization methods and stability estimates are required.
In this article, some efficient regularization BEM, RBM, CHIEF and hypersingular formulation, in conjunction with SVD technique, are employed to study and cope with the rank-deficiency problem numerically.
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