Study on the fiber-optic perimeter sensor signal processor based on neural network classifier

摘要：

Presents a fiber-optic sensing alarm signal processing technology. It has great marketing demand because of the Optical-fiber sensor with high sensitivity, anti-electromagnetic interference, high corrosion resistance, etc. However, it is a problem about the false alarm to system. We use wavelet noise reduction technology and time-frequency domain features to construct the probabilistic neural network classifiers. The result shows it can largely reduce the false signals alarm.

关键词： optical fiber sensor wavelet denoising neural network.

作者: Wu Liang

作者单位: School of Management and Economics,Guizhou Normal University,Guiyang 550001,China;School of Management and Economics,University of Electronic Science and Technology of China,Chengdu 610054,China

会议类型: 国际会议

会议名称: 2011 10th International Conference on Electronic Measurement & Instruments(第十届电子测量与仪器国际会议 ICEMI2011)

会议地点: 成都

会议语种:英文

页码: 93-97

在线出版日期: 2011-08-16（万方平台首次上网日期，不代表论文的发表时间）