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.
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页码：377 / 386
页数：10
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