Open AccessAnalysis of the Wiener filters application to the spectral fluctuation patterns segmentation
Author(s) -
Melinda Melinda,
Elizar Elizar,
Yunidar Yunidar,
Muhammad Irhamsyah
Publication year - 2020
Publication title -
jurnal teknologi dan sistem komputer
Language(s) - English
Resource type - Journals
eISSN - 2620-4002
pISSN - 2338-0403
DOI - 10.14710/jtsiskom.2020.13868
Subject(s) - wiener filter , filter (signal processing) , noise (video) , mathematics , adaptive filter , signal (programming language) , root raised cosine filter , digital filter , pattern recognition (psychology) , computer science , artificial intelligence , algorithm , computer vision , image (mathematics) , programming language
The Wiener filter is an adaptive filter which able to produce the desired estimates. Besides, this filter can also suppress noise in digital signal processing. This study aims to segment the fluctuation pattern, which results from data acquisition from a capacitive sensor with the object H2O. The fluctuation pattern to be processed is the High Fluctuation (HF) pattern by dividing the pattern into several segments according to the input frequency. It aims to see in more detail and clearly the state of each segmentation of the pattern. The results will show noise attenuation and suppression after filtering with a Wiener filter. The Signal to Noise Ratio (SNR) value will also be analyzed, which shows that the signal quality is getting better after applying the Wiener filter. Then, the analysis of the Mean Square Error (MSE) results can provide more consistent results with a smaller average error.