题目: Reduced-order Methods and applications 

摘要: Model Reduction methods developed for data analysis and scientific computing are among the most important enhancing numerical tools in deriving fast and reliable solutions to large scale problems.We introduce in these lectures some of data reduction methods. We will start with the bivariate case for which we w the present and analyze : Proper Orthogonal Decomposition; Proper Generalized Decomposition and Singular Values Decomposition. We will continue mutivraiate case using Recursive Proper Orthogonal Decomposition; High Order Singular Values Decomposition. 

The last part of the course will be dedicated to the reduced basis and how we use them to solve some PDE like for example; High Reynolds number flow dynamics inside a singular lid driven cavity. 

课程安排：

第一次：3月16日下午15:00-17:30  实验楼108

第二次：3月23日下午15:00-17:30  实验楼108

第三次：3月26日下午15:00-17:30  实验楼105

第四次：3月27日下午15:00-17:30  实验楼105

第五次：3月28日上午10:00-12:00  实验楼105