当前位置: 首页 > 学术报告
Riemannian Mean of Positive Definite Matrices
Rajendra Bhatia 教授(印度统计研究所)
2018-01-01 12:13  华东师范大学

曹锡华数学论坛

主办单位:数学系 科技处

报告人简介:Rajendra Bhatia是印度统计研究所教授,印度国家科学院院士,在矩阵分析和算子理论领域做出过很多重要的工作,在Springer,SIAM和Princeton大学出版社出版了3本专著,担任过两本杂志SIAM J. Matrix Anal. Appl. 和 Linear Appl. Appl. 的编委。

报告内容简介: Averaging operations are important in several contexts. A long-standing problem of defining a suitable geometric mean of several positive definite matrices was solved about 10 years ago using ideas from Riemannian geometry. This mean has pleasing geometric and operator-theoretic properties, and is also finding applications in diverse areas like radar data processing, brain mapping, machine learning etc. We will give a brief introduction to the topic.

主持人:詹兴致 教授