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The energy functional of the proposed model consists of three terms, i.e., the patch-statistical region fitting term, the improved regularization term, and the intensity variation penalization term.
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As an inverse problem, the stability of GIB can be improved with regularization methods.
Second, a point injection strategy is designed to improve the regularization capability of feature selection.
Conducting Bayesian learning shall compensate the variations of the estimated parameters and accordingly improve model regularization.
Then, the back-propagation artificial neural network (BPANN) is proposed to recognize different facial movement patterns and improved by Bayesian regularization and Levenberg-Marquardt (LM) algorithm.
After their construction where their accuracy is improved through a regularization process, a localization of these operators and a full finite element approximation is introduced.
Finally, we performed a fluorescence-guided hemoglobin-DOT experiment and demonstrated that the reconstruction accuracy in hemoglobin-DOT could be significantly improved by the regularization of a priori fluorescence location.
Variances are improved considerably by Tikhonov regularization compared with Eq. (20); in the following, to gain a better sense about prediction power of optimized PFE, the testing set is applied again in order to evaluate the new PFE [Eq. (28)].
Finally, the use of regularization significantly improved the performance of the optimization method, resulting in faster and more stable convergence.
Our results in this paper extend and improve the alternative regularization methods proposed by HK Xu.
Numerical experiments show that the l p sparsity regularization improves the spatial resolution.
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