Approximation of Basic Probability Assignment in Dempster-Shafer Theory Based on Correlation Coefficient

被引：0

作者：

Shou, Yehang ^{[1
]}

Deng, Xinyang ^{[1
]}

Liu, Xiang ^{[2
,3
]}

Zheng, Hanqing ^{[3
]}

Jiang, Wen ^{[1
]}

机构：

[1] Northwestern Polytech Univ, Sch Elect & Informat, Xian 710072, Shaanxi, Peoples R China

[2] CASC, Infrared Deqtect Technol Res & Dev Ctr, Shanghai 200233, Peoples R China

[3] Shanghai Inst Spaceflight Control Technol, Shanghai 200233, Peoples R China

来源：

2017 20TH INTERNATIONAL CONFERENCE ON INFORMATION FUSION (FUSION) | 2017年

基金：

中国国家自然科学基金;

关键词：

Dempster-Shafer theory; Belief functions; Basic Probability Assignment; Approximation; Correlation Coefficient; COMBINATION; FUSION;

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：

Dempster-Shafer (D-S) evidence theory is widely used for information fusion field. However, one of the main issues of D-S evidence theory is that, when large amount of focal elements in Basic Probability Assignment (BPA) are available, the fusion of BPA requires high computational cost and long computing time. This problem greatly limits its application. In this paper, a novel method for approximating a BPA based on correlation coefficient is present, which can reduce the computational cost of evidence combination effectively. At last, several numerical examples are given to illustrate the superiority of the proposed method.

引用

页码：535 / 541

页数：7

共 29 条

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