Classification of Human Postures Using Ultra-Wide Band Radar Based on Neural Networks

被引：0

作者：

Kiasari, Mohammad Ahangar ^{[1
]}

Na, Seung You ^{[1
]}

Kim, Jin Young ^{[1
]}

机构：

[1] Chonnam Natl Univ, Dept Elect & Comp Engn, Gwangju, South Korea

来源：

2014 INTERNATIONAL CONFERENCE ON IT CONVERGENCE AND SECURITY (ICITCS) | 2014年

关键词：

UWB Radar system; Neural Network classification; Cumulant;

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：

For the last few years, many papers have worked on UWB radar technology for the target detection. Recognition of the human posture could be the next important study. Experimental studies are undertaken with a novel method of the ultra-wideband (UWB) systems to conceal obstacle detection and classification. The recognition can be achieved by UWB-IR signals. In this paper, some features have been presented based on the Cumulant theory to consider the possibility of categorizing different human posture like standing, sitting and lying targets. This paper has used Matlab Neural Network toolbox to do the classification.

引用

页数：4

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