反问题的非线性滤波研究进展

IF 0.3 Q4 MATHEMATICS Communications in Applied and Industrial Mathematics Pub Date : 2022-01-01 DOI:10.48550/arXiv.2204.02253

M. Herty, E. Iacomini, G. Visconti

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引用次数: 0

摘要

在一类非线性粒子滤波方法中，集成卡尔曼滤波(EnKF)因其用于求解逆问题而受到近年来的关注。我们回顾了原来的方法，并讨论了最近的发展，特别是考虑到无限粒子的极限和向稳定性分析和多目标优化的扩展。我们用文献中的测试反问题来说明该方法的性能。

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Recent Trends on Nonlinear Filtering for Inverse Problems

Abstract Among the class of nonlinear particle filtering methods, the Ensemble Kalman Filter (EnKF) has gained recent attention for its use in solving inverse problems. We review the original method and discuss recent developments in particular in view of the limit for infinitely particles and extensions towards stability analysis and multi–objective optimization. We illustrate the performance of the method by using test inverse problems from the literature.

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来源期刊

Communications in Applied and Industrial Mathematics Mathematics-Applied Mathematics

CiteScore

1.30

自引率

0.00%

发文量

审稿时长

16 weeks

期刊介绍： Communications in Applied and Industrial Mathematics (CAIM) is one of the official journals of the Italian Society for Applied and Industrial Mathematics (SIMAI). Providing immediate open access to original, unpublished high quality contributions, CAIM is devoted to timely report on ongoing original research work, new interdisciplinary subjects, and new developments. The journal focuses on the applications of mathematics to the solution of problems in industry, technology, environment, cultural heritage, and natural sciences, with a special emphasis on new and interesting mathematical ideas relevant to these fields of application . Encouraging novel cross-disciplinary approaches to mathematical research, CAIM aims to provide an ideal platform for scientists who cooperate in different fields including pure and applied mathematics, computer science, engineering, physics, chemistry, biology, medicine and to link scientist with professionals active in industry, research centres, academia or in the public sector. Coverage includes research articles describing new analytical or numerical methods, descriptions of modelling approaches, simulations for more accurate predictions or experimental observations of complex phenomena, verification/validation of numerical and experimental methods; invited or submitted reviews and perspectives concerning mathematical techniques in relation to applications, and and fields in which new problems have arisen for which mathematical models and techniques are not yet available.