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All Journal Perfecting a Video Game with Game Metrics Jurnal INFOTEL
Ponco Siwindarto
Brawijaya University
Computer Science & IT Electrical & Electronics Engineering

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Nonlinearity compensation of low-frequency loudspeaker response using internal model controller Erni Yudaningtyas; Achsanul Khabib; Waru Djuriatno; Dionysius J. D. H. Santjojo; Adharul Muttaqin; Ponco Siwindarto; Zakiyah Amalia
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 17, No 2: April 2019
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v17i2.11761

Abstract

This paper presents the nonlinearity compensation of low-frequency loudspeaker response. The loudspeaker is dedicated to measuring the response of Electret Condenser Microphone which operated in the arterial pulse region. The nonlinearity of loudspeaker has several problems which cause the nonlinearity behaviour consists of the back electromagnetic field, spring, mass of cone and inductance. Nonlinearity compensation is done using the Internal Model Controller with voltage feedback linearization. Several signal tests consist of step, impulse and sine wave signal are examined on different frequencies to validate the effectiveness of the design. The result showed that the Internal Mode Controller can achieve the high-speed response with a small error value.
Investigation of Human Emotion Pattern Based on EEG Signal Using Wavelet Families and Correlation Feature Selection Dwi Utari Surya; Ponco Siwindarto; Erni Yudaningtyas
JURNAL INFOTEL Vol 11 No 2 (2019): May 2019
Publisher : LPPM INSTITUT TEKNOLOGI TELKOM PURWOKERTO

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.20895/infotel.v11i2.431

Abstract

Emotions is one of the advantages given by God to human beings compared to other living creatures. Emotions have an important role in human life. Many studies have been conducted to recognize human emotions using physiological measurements, one of which is Electroencephalograph (EEG). However, the previous researches have not discussed the types of wavelet families that have the best performance and canals that are optimal in the introduction of human emotions. In this paper, the power features of several types of wavelet families, namely Daubechies, symlets, and coiflets with the Correlation Feature Selection (CFS) method to select the best features of alpha, beta, gamma and theta frequencies. According to the results, coiflet is a method of the wavelet family that has the best accuracy value in emotional recognition. The use of the CFS feature selection can improve the accuracy of the results from 81% to 93%, and the five most dominant channels in the power features of alpha and gamma band on T8, T7, C5, CP5, and TP7. Hence, it can be concluded that the temporal of the left brain is more dominant in recognition of human emotions.
Co-Authors Achsanul Khabib Adharul Muttaqin Dionysius J. D. H. Santjojo Dwi Utari Surya Erni Yudaningtyas Waru Djuriatno Zakiyah Amalia