EMPIRICAL MODE DECOMPOSITION BASED SUPPORT VECTOR MACHINES FOR MICROEMBOLI CLASSIFICATION

被引：0
|
作者：
Ferroudji, K. [1 ,2 ]
Benoudjit, N. [1 ,3 ]
Bouakaz, A.
机构：
[1] Univ Batna, Dept Elect, Batna, Algeria
[2] CDTA, A-16303 Algiers, Algeria
[3] CNRS, UMR Inserm, Tours, France
来源：
2013 8TH INTERNATIONAL WORKSHOP ON SYSTEMS, SIGNAL PROCESSING AND THEIR APPLICATIONS (WOSSPA) | 2013年
关键词：
NEAREST-NEIGHBOR; RECOGNITION; RISK;
D O I：
暂无
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
The classification of circulating microemboli, in the bloodstream, as gaseous or particulate matter is vital for selecting appropriate treatment for patients. Until now, Doppler techniques have shown some limitations to determine clearly the nature of circulating microemboli. The fraditional techniques are largely based on the Fourier analysis. In this paper we present new emboli detection method based on Empirical mode decomposition and support vector machine using Radio Frequency (RF) signal instead of Doppler signals.
引用
收藏
页码：84 / 88
页数：5
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