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Oktafiandi, Aulia
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Computer Science & IT Electrical & Electronics Engineering

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PEREDUKSIAN ADDITIVE WHITE GAUSSIAN NOISE (AWGN) PADA SINYAL DATA MENGGUNAKAN DENOISING KOEFISIEN DARI TRANSFORMASI WAVELET Saragih, Riko Arlando; Oktafiandi, Aulia
Jurnal Telematika Vol. 5 No. 1 (2009)
Publisher : Yayasan Petra Harapan Bangsa

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61769/telematika.v5i1.34

Abstract

Noise presence in real world data signal is inevitable.Under ideal conditions, this noise may decrease to such negligiblelevels so data obtained might be considered not corrupted by noise.In denoising, wavelet attempts to remove the noise present in thesignal while preserving the signal characteristics. It involves threesteps, namely forward wavelet transform, thresholding step, andinverse wavelet transform.Based on simulations by using Hard Thresholding and SureShrinkwith Empirical Wiener Filter, it was shown that Empirical WienerFilter using Hard Thresholded outperforms the other simulatedmethods.
Co-Authors Riko Arlando Saragih