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International Journal for Uncertainty Quantification

Publicou 6 edições por ano

ISSN Imprimir: 2152-5080

ISSN On-line: 2152-5099

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.7 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 1.9 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.5 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.0007 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.5 SJR: 0.584 SNIP: 0.676 CiteScore™:: 3 H-Index: 25

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NUMERICAL SOLUTIONS FOR FORWARD BACKWARD DOUBLY STOCHASTIC DIFFERENTIAL EQUATIONS AND ZAKAI EQUATIONS

Volume 1, Edição 4, 2011, pp. 351-367
DOI: 10.1615/Int.J.UncertaintyQuantification.2011003508
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RESUMO

The numerical solutions of decoupled forward backward doubly stochastic differential equations and the related stochastic partial differential equations (Zakai equations) are considered. Numerical algorithms are constructed using reference equations. Rate of convergence is obtained through rigorous error analysis. Numerical experiments are carried out to verify the rate of convergence results and to demonstrate the efficiency of the proposed numerical algorithms.

CITADO POR
  1. Bao Feng, Cao Yanzhao, Zhao Weidong, A first order semi-discrete algorithm for backward doubly stochastic differential equations, Discrete and Continuous Dynamical Systems - Series B, 20, 5, 2015. Crossref

  2. Bao Feng, Cao Yanzhao, Meir Amnon, Zhao Weidong, A First Order Scheme for Backward Doubly Stochastic Differential Equations, SIAM/ASA Journal on Uncertainty Quantification, 4, 1, 2016. Crossref

  3. Bachouch Achref, Matoussi Anis, L2-regularity result for solutions of backward doubly stochastic differential equations, Stochastics and Dynamics, 20, 02, 2020. Crossref

  4. Archibald Richard, Bao Feng, Yong Jiongmin, Zhou Tao, An Efficient Numerical Algorithm for Solving Data Driven Feedback Control Problems, Journal of Scientific Computing, 85, 2, 2020. Crossref

  5. Li Xin, Bao Feng, Gallivan Kyle, A drift homotopy implicit particle filter method for nonlinear filtering problems, Discrete & Continuous Dynamical Systems - S, 15, 4, 2022. Crossref

  6. Teng Bin, Shi Yufeng, Zhu Qingfeng, Solving high-dimensional forward-backward doubly SDEs and their related SPDEs through deep learning, Personal and Ubiquitous Computing, 26, 4, 2022. Crossref

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