Computational inverse problems, optimization, differential equations and applications

计算反问题、优化、微分方程和应用

• 批准号: RGPIN-2016-03855
• 负责人: Ascher, Uri
• 金额: $ 3.35万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634655
• 关键词: Computational; inverse; problems; optimization; differential

The general objective of my research is to develop efficient and reliable computational algorithms for large-scale models involving surface reconstruction, inference problems and differential equations that arise in applications. The focus is on methods for randomization, optimization and constrained differential problems, such as those arising in 3D digital geometry and tracking, image processing, model calibration, virtual reality simulations and distributed parameter estimation.

我研究的总体目标是为涉及表面重建、推理问题和应用中出现的微分方程的大规模模型开发高效可靠的计算算法。重点是随机化、优化和约束微分问题的方法，例如在三维数字几何和跟踪、图像处理、模型校准、虚拟现实仿真和分布参数估计中出现的问题。