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All Journal International Journal of Electrical and Computer Engineering Jurnal Elektronika dan Telekomunikasi
Chaeriah Bin Ali Wael, Chaeriah Bin
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Computer Science & IT Electrical & Electronics Engineering Engineering

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Infinite Latent Feature Selection Technique for Hyperspectral Image Classification Miftahushudur, Tajul; Ali Wael, Chaeriah Bin; Praludi, Teguh
Jurnal Elektronika dan Telekomunikasi Vol 19, No 1 (2019)
Publisher : Indonesian Institute of Sciences

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.14203/jet.v19.32-37

Abstract

The classification process is one of the most crucial processes in hyperspectral imaging. One of the limitations in classification process using machine learning technique is its complexities, where hyperspectral image format has a thousand band that can be used as a feature for learning purpose. This paper presents a comparison between two feature selection technique based on probability approach that not only can tackle the problem, but also improve accuracy. Infinite Latent Feature Selection (ILFS) and Relief Techniques are implemented in a hyperspectral image to select the most important feature or band before applied in Support Vector Machine (SVM). The result showed ILFS technique can improve classification accuracy better than Relief (92.21% vs. 88.10%). However, Relief can extract less feature to reach its best accuracy with only 6 features compared with ILFS with 9.
Impact of carrier frequency offset and in-phase and quadrature imbalance on the performance of wireless precoded orthogonal frequency division multiplexing Suyoto, Suyoto; Subekti, Agus; Satyawan, Arief Suryadi; Armi, Nasrullah; Ali Wael, Chaeriah Bin; Nurkahfi, Galih Nugraha
International Journal of Electrical and Computer Engineering (IJECE) Vol 12, No 5: October 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v12i5.pp5153-5163

Abstract

Precoding in orthogonal frequency division multiplexing (OFDM) system proved to reduce the peak-to-average power ratio (PAPR), so that it improves BER. However, from the existing literature, the effect of carrier frequency offset (CFO), in-phase and quadrature (IQ) imbalance on precoded wireless OFDM systems has not been carried out. Therefore, this study evaluated the precoded OFDM (P-OFDM) system performance by considering the impact of CFO and IQ imbalance. P-OFDM performance evaluation is expressed in signal-to-interference noise ratio (SINR) and bit error rates (BER). The communication channels used are the additive white Gaussian noise (AWGN) channel and the frequency-selective Rayleigh fading (FSRF) channel, while the channel equalization process is considered perfect. The results of the analysis and simulation show that P-OFDM is greater affected by the presence of CFO and IQ imbalance than conventional OFDM system. In AWGN channel, P-OFDM experiences different SINR for each subcarrier. This is different from conventional OFDM system, where all SINRs are the same for all subcarriers. In the FSRF channel, both the POFDM system and the OFDM system experience different SINR for each subcarrier, where the SINRs fluctuation in the P-OFDM system is much larger than in the OFDM system.
Co-Authors Agus Subekti Miftahushudur, Tajul Nasrullah Armi Nurkahfi, Galih Nugraha Satyawan, Arief Suryadi Suyoto Suyoto Teguh Praludi