The comparison of threshold techniques in one-cycle sliding window length for transient event / Saidatul Habsah Asman, Nofri Yenita Dahlan and Ahmad Farid Abidin
Wavelet transform (WT) is an effective method to denoise the signal based on several attainment de-noising through wavelet threshold methods. In this study, four types threshold technique namely rigrsure, minimaxi, heursure, and sqtwolog as proposed have been tested to de-noise the signal with t...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
UiTM Press
2018
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| Subjects: | |
| Online Access: | https://ir.uitm.edu.my/id/eprint/63055/1/63055.pdf https://ir.uitm.edu.my/id/eprint/63055/ https://jeesr.uitm.edu.my/v1/ |
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| Summary: | Wavelet transform (WT) is an effective method to denoise the signal based on several attainment de-noising through
wavelet threshold methods. In this study, four types threshold
technique namely rigrsure, minimaxi, heursure, and sqtwolog
as proposed have been tested to de-noise the signal with
transient event. This study has been focusing on decomposition
coefficient at all levels signals for analysis. The mean square
error (MSE) and correlation coefficient (CC) are evaluated to
indicate the performance of proposed threshold. The analysis
signal is simulated using signal processing tool. From the
analysis, rigrsure is the best threshold that can be used for denoising signals with transient event because it is performed the
highest CC and lowest MSE for both one-cycle sliding window
and total 21 cycles reconstructed coefficient. |
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