3rd international workshop on new computational methods for inverse problems (NCMIP 2013)

作     者：Blanc-Féraud, Laure Joubert, Pierre-Yves 

出 版 物：《Journal of Physics: Conference Series》 (J. Phys. Conf. Ser.)

年 卷 期：2013年第464卷第1期

核心收录：

学科分类：07[理学] 0702[理学-物理学] 

基　　金：The PRET+ study and isolate collection were funded by a grant from the Bill & Melinda Gates Foundation  Seattle  WA  USA (no. 48027)  an unrestricted grant from Research to Prevent Blindness and a grant from the Johns Hopkins Global Water Program. The sequencing and analysis component of the project was funded in part by federal funds from the National Institute of Allergy and Infectious Diseases  National Institutes of Health  Department of Health and Human Services  under contract number HHSN272200900009C  grant number U19AI110820  and National Institute of Diabetes and Digestive and Kidney Diseases 2T32DK067872-11 (T.K.S.R.) 

摘      要：This volume of Journal of Physics: Conference Series is dedicated to the scientific contributions presented during the 3rd International Workshop on New Computational Methods for Inverse Problems, NCMIP 2013 (http://***/NCMIP_***). This workshop took place at Ecole Normale Supérieure de Cachan, in Cachan, France, on 22 May 2013, at the initiative of Institut Farman. The prior editions of NCMIP also took place in Cachan, France, firstly within the scope of the ValueTools Conference, in May 2011 (http://***/2011/), and secondly at the initiative of Institut Farman, in May 2012 (http://***/NCMIP_***). The NCMIP Workshop focused on recent advances in the resolution of inverse problems. Indeed inverse problems appear in numerous scientific areas such as geophysics, biological and medical imaging, material and structure characterization, electrical, mechanical and civil engineering, and finances. The resolution of inverse problems consists of estimating the parameters of the observed system or structure from data collected by an instrumental sensing or imaging device. Its success firstly requires the collection of relevant observation data. It also requires accurate models describing the physical interactions between the instrumental device and the observed system, as well as the intrinsic properties of the solution itself. Finally, it requires the design of robust, accurate and efficient inversion algorithms. Advanced sensor arrays and imaging devices provide high rate and high volume data; in this context, the efficient resolution of the inverse problem requires the joint development of new models and inversion methods, taking computational and implementation aspects into account. During this one-day workshop, researchers had the opportunity to bring to light and share new techniques and results in the field of inverse problems. The topics of the workshop were: algorithms and computational aspects of invers