Noise cancellation in gamelan signal by using least mean square based adaptive filter

Mamba’us Sa’adah; Diah Puspito Wulandari; Yoyon Kusnendar Suprapto

doi:10.5013/IJSSST.a.19.03.17

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Noise cancellation in gamelan signal by using least mean square based adaptive filter

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Mamba’us Sa’adah, Diah Puspito Wulandari, Yoyon Kusnendar Suprapto

2018 International Journal of Simulation: Systems, Science and Technology Vol. 19 Issue 3 Article Cited by 3

Abstract

Gamelan is one of Indonesian traditional music instrument that has been worldwide. Noise reduction of identical instrument is a key challenge for instrument recognition, music processing and instrument analysis. Many theoretical analysis and experiments have been carried out to show that the optimal filtering technique can reduce the level of noise that is present in the instrument signal. In this paper, we conducted a study for noise removal on gamelan instruments using least-mean-square (LMS). Using the original signal mixed with noise, the result that enlarging the rate of convergence, filter order, and iteration can improve the LMS function in noise removal in the instrument gamelan. The performance of the designed adaptive filter is evaluated based on the mean square error by varying the additive white Gaussian noise levels. We found that the performance of Least Mean Square is satisfactory and is viable to be applied in gamelan signal. © 2018, UK Simulation Society. All rights reserved.

Affiliations

Departement of Electrical Engineering, Institut Teknologi Sepuluh Nopember, Surabaya, Indonesia; Universitas Widyagama, Malang, Indonesia

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