A Robust Algorithm for Selecting Optimal Regularization Parameter Based on Bilateral Accumulative Area

摘要

The choice of regularization parameters is very important for the reconstruction result in the inverse problem of electrocardiology. In this study, the bilateral accumulative area detector is introduced to estimate the optimal parameter points of the L-curve and Generalized Cross-Validation method to Tikhonov regularization and truncated singular value decomposition. The experimental results suggest that this method can achieve high validity and high robustness for the estimation of regularization parameters compared to conventional methods.