The Comparison of Threshold Techniques in One-Cycle Sliding Window Length for Transient Event

Wavelet transform (WT) is an effective method to de-noise 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 de-noising 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