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

研究培训组的论文项目都可以归入“数学模型识别”的主题。这包括经典的反问题偏微分方程（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），并结合这两个领域，在数学和应用中的新的识别和分类问题（例如随机过程的分类、指纹的几何识别、外来基因的识别）。这些主题涵盖了广泛的数学理论问题，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。

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.