Improved kernel density estimation for clustered data using regularisation and deconvolution

被引：0

作者：

Chen, Q ^{[1
]}

Sandoz, D ^{[1
]}

Wynne, RJ ^{[1
]}

Kruger, U ^{[1
]}

机构：

[1] Univ Manchester, Manchester, Lancs, England

来源：

PROCEEDINGS OF THE 2000 AMERICAN CONTROL CONFERENCE, VOLS 1-6 | 2000年

关键词：

multivariate statistics; kernel density estimation; condition monitoring; regularisation; deconvolution; cross validation;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To extract multivariate Probability Density Function (PDF) form clustered training data set for condition monitoring purpose, a modified kernel density estimation method is suggested using regularisation and deconvolution techniques. Case studies show that it is a useful pragmatic method for real industrial data.

引用

页码：1410 / 1414

页数：5

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