DocumentCode :
2543358
Title :
A Comparison of different methods for choosing regularization parameter in regularized MT inversion
Author :
Xiang Yang ; Yu Peng ; Chen Xiao ; Zhang Xu ; Tang Rui
Author_Institution :
State Key Lab. of Marine Geol., Tongji Univ., Shanghai, China
fYear :
2012
fDate :
29-31 May 2012
Firstpage :
2533
Lastpage :
2536
Abstract :
Geophysical inversion is ill-posed. We can get a stable result not only from high resolution observed data, but also using the regularization methods to add stabilizing functional to increase the stability of the solution. The conjugate gradient method is used in Occam´s inversion to improve the efficiency of inversion operator. By establishing a layered electric model, we use L-curve, GCV (Generalized Cross Validation) and UPRE (Unbiased Predictive Risk Estimator) to select the optimal regularized parameter. Through analyzing the characteristic of each ways, L-curve method is very stable and the result is appreciable, the result of GCV or UPRE is also well and tends to overfit the data slightly.
Keywords :
conjugate gradient methods; geophysical techniques; inverse problems; magnetotellurics; risk analysis; GCV; Generalized Cross Validation; L-curve; Occam inversion; UPRE; Unbiased Predictive Risk Estimator; conjugate gradient method; geophysical inversion; inversion operator; layered electric model; optimal regularized parameter; regularization parameter methods; regularized MT inversion; Computational modeling; Conductivity; Data models; Gradient methods; Inverse problems; Magnetic resonance imaging; Mathematical model; GCV; L-curve method; Occam´s inversion; UPRE; conjugate gradient; magnetotelluric(MT); optimal regularized parameter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems and Knowledge Discovery (FSKD), 2012 9th International Conference on
Conference_Location :
Sichuan
Print_ISBN :
978-1-4673-0025-4
Type :
conf
DOI :
10.1109/FSKD.2012.6233848
Filename :
6233848
Link To Document :
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