ESTIMATION, PRINCIPAL COMPONENTS AND HAMILTONIAN-SYSTEMS

被引：8

作者：

BLOCH, A ^{[1
]}

机构：

[1] HARVARD UNIV,DIV APPL SCI,CAMBRIDGE,MA 02138

来源：

SYSTEMS & CONTROL LETTERS | 1985年 / 6卷 / 02期

关键词：

D O I：

10.1016/0167-6911(85)90005-2

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper we show how symplectic geometry can be used to analyze a fundamental problem in estimation theory - the fitting of lines and planes to a data set in n dimensions. Symplectic methods yield information not only on the critical point structure of the Maximum Likelihood Estimation (MLE) function, but also on the asymmetries in the distribution of the data points in n-space.

引用

页码：103 / 108

页数：6

共 26 条

[1] COMPLETELY INTEGRABLE SYSTEMS, EUCLIDEAN LIE-ALGEBRAS, AND CURVES [J].