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Averaging principle for fast-slow system driven by mixed fractional Brownian rough path

报告人: Bin Pei, School of Mathematics and Statistics, Northwestern Polytechnical University

报告时间:7.5日 09:50-11:00

报告地点:腾讯视频会议 128 444 709

报告人简介:裴斌,博士,教授,德国洪堡学者,日本学术振兴会特别研究员(JSPS Fellow),复旦大学超级博士后。主要从事应用概率统计、非线性随机动力学、随机分析与控制的科学研究工作,入选陕西省高校科协青年人才托举计划(2022-2023),主持国家自然科学基金青年项目 1 项,省部级项目 1 项,日本 JSPS 特别资助 1 项,中央高校基本科研业务费项目1 项,西北工业大学优秀博士奖励基金 1 项 (全校仅9人)、西北工业大学博士创新基金 1 项,作为重要完成人参加国家自然科学基金面上项目 3 项。近五年发表 SCI 检索的高水平科研论文 20 余篇,ESI高被引论文 2 篇,博士论文被评为“陕西省优秀博士学位论文”。

报告内容简介:This work is devoted to studying the averaging principle for fast-slow system of rough differential equations driven by mixed fractional Brownian rough path. The fast component is driven by Brownian motion, while the slow component is driven by fractional Brownian motion with Hurst index H (1/3 < H ≤ 1/2). Combining the fractional calculus approach to rough path theory and Khasminskii's classical time discretization method, we prove that the slow component strongly converges to the solution of the corresponding averaged equation in the L1-sense. The averaging principle for a fast-slow system in the framework of rough path theory seems new.


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