A mutual information based distance for multivariate Gaussian processes

被引：0

作者：

Boets, Jeroen ^{[1
]}

De Cock, Katrien ^{[1
]}

De Moor, Bart ^{[1
]}

机构：

[1] Katholieke Univ Leuven, Dept Elect Engn, ESAT SCD, Kasteelpk Arenberg 10, B-3001 Louvain, Belgium

来源：

MODELING, ESTIMATION AND CONTROL: FESTSCHRIFT IN HONOR OF GIORGIO PICCI ON THE OCCASION OF THE SIXTY-FIFTH BIRTHDAY | 2007年 / 364卷

关键词：

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：

In this paper a new distance on the set of multivariate Gaussian linear stochastic processes is proposed based on the notion of mutual information. The definition of the distance is inspired by various properties of the mutual information of past and future of a stochastic process. For two special classes of stochastic processes this mutual information distance is shown to be equal to a cepstral distance. For general multivariate processes, the behavior of the mutual information distance is similar to the behavior of an ad hoc defined multivariate cepstral distance.

引用

页码：15 / +

页数：4

共 34 条

[1] MARKOVIAN REPRESENTATION OF STOCHASTIC-PROCESSES BY CANONICAL VARIABLES [J].