GRK 1023: Identification in Mathematical Models: Synergy of Stochastic and Numerical Methods

GRK 1023：数学模型中的识别：随机方法和数值方法的协同作用

• 批准号: 373214
• 金额: --
• 依托单位: Georg-August-Universität Göttingen
• 依托单位国家: 德国
• 项目类别: Research Training Groups
• 财政年份: 2004
• 资助国家: 德国
• 起止时间: 2003-12-31 至 2012-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/373214?language=en
• 关键词: GRK; 1023; Identification; Mathematical; Models

The dissertation projects of the Research Training Group can all be subsumed under the theme "Identification in Mathematical Models". This includes classical inverse problems for partial differential equations (for example, inverse scattering theory and impedance tomography), classical parameter and model identification in statistics (for example by statistical learning algorithms) and, combining the two preceeding areas, new identification and classification problems in mathematics and in applications (for example classification of stochastic processes, geometric identification of fingerprints, identification of alien genes). The topics cover a broad range connecting theoretical mathematical problems, application relevant problems from numerical analysis and statistics, and interdisciplinary projects in collaboration with members of other sciences.

研究训练组的论文项目都可以归入“数学模型中的识别”这一主题。这包括偏微分方程的经典反问题（例如，逆散射理论和阻抗层析成像），统计学中的经典参数和模型识别（例如，通过统计学习算法），以及结合前面两个领域，数学和应用中的新识别和分类问题(例如，随机过程的分类，指纹的几何识别，外来基因的鉴定)。主题涵盖了广泛的理论数学问题，数值分析和统计的应用相关问题，以及与其他科学成员合作的跨学科项目。