@inproceedings{dbee6e8c430c44ae8623ae6b63364b7f,
title = "Time-frequency analysis of electrostatic discharge signal based on wavelet transform",
abstract = "Electrostatic discharge signal is a non-stationary signal whose frequency is varied with time. Time-frequency analysis is able to reveal the more useful information hidden in the ESD signal. In this letter, we propose a time-frequency analysis approach using the wavelet transform. Based on the Morlet wavelet, this paper analyzes the actual ESD signal and obtains its time-frequency characteristic. 2-D and 3-D ESD data are showed in this paper. The result shown that high frequency component of ESD can reach 0.6GHz. In addition, the energy of the measured signal is mainly concentrated in the range of 100 to 200 MHz. The high-frequency component attenuations rapidly and the low-frequency duration is relatively long. It can provide some new idea for extraction or signal denoising.",
keywords = "Electrostatic discharge, Time-frequency analysis, Wavelet transform",
author = "Cong Cheng and Fangming Ruan and Di Deng and Jia Li and Ming Su and David Pommerenke",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ICASID.2018.8693107",
language = "English",
series = "Proceedings of the International Conference on Anti-Counterfeiting, Security and Identification, ASID",
publisher = "IEEE Computer Society",
pages = "35--38",
booktitle = "Proceedings of 2018 12th IEEE International Conference on Anti-Counterfeiting, Security, and Identification, ASID 2018",
address = "United States",
note = "12th IEEE International Conference on Anti-Counterfeiting, Security, and Identification, ASID 2018 ; Conference date: 09-11-2018 Through 11-11-2018",
}