@inproceedings{edd555c57b524129a6d387286edfeac3,
title = "Research on wavelet threshold de-noising method of remainder detection for stand-alone electronic equipments in satellite",
abstract = "Stand-alone electronic equipments are important parts of a satellite system, inside which remainders will bring great harm to reliability of the satellite system. Particle shock noise detection (PIND) is an effective method to detect the remainders in stand-alone electronic equipments. Signal to noise ratio (SNR) of detection signal is a bottleneck to improve processing accuracy and robustness of testing software. In this paper, key factors of wavelet threshold de-noising method were investigated and a wavelet threshold algorithm was proposed to improve the SNR of remainder detection signal of the standalone electronic equipments. The analytic results proved that the wavelet threshold method efficiently improved the de-noising effect.",
keywords = "Remaider detection, Signal processing, Stand-alone electronic equipments in satellite, Wavelet threshold de-noising method",
author = "Yingga Wu and Shicheng Wang and Shujuan Wang",
year = "2010",
doi = "10.1109/PCSPA.2010.250",
language = "英语",
isbn = "9780769541808",
series = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",
pages = "1013--1017",
booktitle = "Proceedings - 2010 1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010",
note = "1st International Conference on Pervasive Computing, Signal Processing and Applications, PCSPA 2010 ; Conference date: 17-09-2010 Through 19-09-2010",
}