Multi-level statistical analysis of high-frequency spatio-temporal process data (C03)

高频时空过程数据多层次统计分析（C03）

• 批准号: 192961513
• 金额: --
• 依托单位: Informatik VIII - Lehrstuhl Künstliche Intelligenz
• 依托单位国家: 德国
• 项目类别: Collaborative Research Centres
• 财政年份: 2011
• 资助国家: 德国
• 起止时间: 2010-12-31 至 2021-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/192961513?language=en
• 关键词: Multi; level; statistical; analysis; frequency

High-frequency high-dimensional process data are typically analyzed in several steps. Interesting data need to be identified and selected in real time for further analysis because of limited storage capacities. By means of the challenging example of detection and classification of astrophysical particles appearing as transient patterns in spatio-temporal data, we want to construct robust generalizable techniques for reduction, classification, and modeling of such data, as well as strategies for the suitable combination of these analysis steps.

高频高维过程数据通常分几个步骤进行分析。由于存储容量有限，需要在真实的时间内识别和选择感兴趣的数据以供进一步分析。通过检测和分类的天体物理粒子出现在时空数据中的瞬态模式的挑战性的例子，我们要构建强大的可推广的技术，减少，分类和建模的数据，以及这些分析步骤的适当组合的策略。