Back to Search Start Over

Exponential weighted entropy and exponential weighted mutual information

Authors :
Shiwei Yu
Ting-Zhu Huang
Source :
Neurocomputing. 249:86-94
Publication Year :
2017
Publisher :
Elsevier BV, 2017.

Abstract

In this paper, the exponential weighted entropy (EWE) and exponential weighted mutual information (EWMI) are proposed as the more generalized forms of Shannon entropy and mutual information (MI), respectively. They are position-related and causal systems that redefine the foundations of information-theoretic metrics. As the special forms of the weighted entropy and the weighted mutual information, EWE and EWMI have been proved that they preserve nonnegativity and concavity properties similar to Shannon frameworks. They can be adopted as the information measures in spatial interaction modeling. Paralleling with the normalized mutual information (NMI), the normalized exponential weighted mutual information (NEWMI) is also investigated. Image registration experiments demonstrate that EWMI and NEWMI algorithms can achieve higher aligned accuracy than MI and NMI algorithms.

Details

ISSN :
09252312
Volume :
249
Database :
OpenAIRE
Journal :
Neurocomputing
Accession number :
edsair.doi...........c6b9c1b2b285faceeadfdbef096a4e3d