Properties of the Cross Entropy Between ARMA Processes

被引：0

作者：

Grivel, Eric ^{[1
]}

机构：

[1] Bordeaux Univ, INP Bordeaux ENSEIRB MATMECA, IMS, UMR CNRS 5218, Talence, France

来源：

GEOMETRIC SCIENCE OF INFORMATION | 2019年 / 11712卷

关键词：

Cross entropy; Jeffreys divergence; Kullback-Leibler divergence; ARMA processes; JEFFREYS DIVERGENCE;

D O I：

10.1007/978-3-030-26980-7_39

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

In this paper, we propose to analyze the properties of the cross entropy between the probability density functions of k consecutive samples of wide-sense stationary Gaussian ARMA processes. It is shown that, when k increases, the cross entropy has a transient behavior before tending to an affine function of k whose slope is defined by the so-called asymptotic increment. The latter depends on the parameters of the processes and can be a reasonable choice to characterize the cross entropy. Some illustrations are then given.

引用

页码：377 / 386

页数：10

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