Earticle

초록

영어

To extract the brainstem auditory evoked potentials and remove the spontaneous electroencephalograph and other background noises, the paper proposed a new method of wavelet information entropy theory de-noising based on wavelet de-noising. In the method, the threshold function is improved by introducing the weighting factor and determine the weighting factor according to the wavelet information entropy to obtain a better de-noising effect. The simulation experiment shows, compared to the traditional wavelet de-noising method, the new method can preserve the details of the signal better and make the signal waveform smoother. At the same time, the new method can suppress the pulse signal, which make the system has a better de-noising performance and achieve higher quality extraction brainstem auditory evoked potentials.

목차

Abstract
 1. Introduction
 2. De-noising and Extracting Algorithm of Wavelet Analysis
 3. Signal Extraction Algorithm based on Wavelet Information Entropy
 4. Simulation Experiment and Analysis
 5. Conclusions
 References

키워드

저자

• Haijun Lin [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Xinlei Wang [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Jia Yu [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]
• Bo Liu [ Higher Education Key Lab for Measuring & Control Technology and Instrumentations of Heilongjiang, Harbin University of Science and Technology, Harbin, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605