Department of Electrical and Electronic Engineering

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About Department of Electrical and Electronic Engineering

Facts about Department of Electrical and Electronic Engineering

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48

Publications

42

Academic Staff

1292

Students

0

Graduates

Programs

B. Sc. in Electronic and Communication Engineering
Major Electronic and Communication Engineering

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B. Sc. in Control and Automation Engineering
Major Control and Automation Engineering

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Who works at the Department of Electrical and Electronic Engineering

Department of Electrical and Electronic Engineering has more than 42 academic staff members

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Dr. wael saleh mohamed abughres

د. وائل صالح أبوغريس هو احد اعضاء هيئة التدريس بقسم بقسم الهندسة الكهربائية والإلكترونية بكلية الهندسة. يعمل د. وائل صالح أبوغريس بجامعة طرابلس كأستأذ مساعد منذ 5 مارس 2017 وله العديد من المنشورات العلمية في مجال تخصصه.

Publications

Some of publications in Department of Electrical and Electronic Engineering

Space-Time Block Coded Spatial Modulation Aided mmWave MIMO with Hybrid Precoding

In this paper, a combination of Space-Time Block Coded Spatial Modulation with Hybrid Analog-Digital Beamforming (STBC-SM-HBF) for Millimeter-wave (mmWave) communications is proposed in order to take advantage of the merits of Spatial Modulation (SM), Space-Time Block Codes (STBC), Analog Beamforming (ABF), and digital precoding techniques while avoiding their drawbacks. This proposed system benefits from the multiplexing gain of SM, from the transmit diversity gain of STBC, and from the Signal-to-Noise Ratio (SNR) gain of the beamformer. The simulation results demonstrate that the Zero Forcing (ZF) and the Minimum Mean Square Error (MMSE) precoded STBC-SM systems have better Bit Error Rate (BER) performance than the precoded SM systems. Moreover, the precoded SM shows a performance degradation compared to STBC-SM system. Furthermore, the BER is significantly improved by employing an array of ABF. In addition, it is demonstrated that a minimum of 2 antenna elements in the proposed scheme of STBC-SM-HBF are required to obtain better BER than that of the conventional SM and STBC-SM systems under the same spectral efficiency of 2 bits/s/Hz.
Taissir Y. Elganimi, Ali A. Elghariani(5-2018)
Publisher's website

Image Transmission Over Erroneous Wireless mobile Channels using HQAM Techniques

AbstractThis paper examines the process of sending an image over wireless mobile Channels with errors while maintaining bandwidth, transmission speed and image quality. With the tremendous development in networks, new wireless channels have been opened that threaten the security of data transmitted through networks and communication channels, and from this emerged Encryption techniques to increase the security of the transmitted data, and since the digital image compression algorithm is a process to reassemble the parts of the image so that it takes less space, but this increases the impact of the error extension in sending compressed digital images and greatly reduces the quality of the received image. This prompts us in this paper to study the performance of HQAM technology for the purpose of transmitting image data over wireless communication channels containing errors. In this paper, image quality performance has been evaluated by the BER, SNR, PSNR, SSIM, and Correlation evaluation criteria. The simulated results show that there is an improvement in the image quality received using the proposed technique.
wael saleh mohamed abughres, , , Ashrf Alzrouk Almagdob1, Ahmed B. Abdurrhman, Ibrahim A.Nasir, (9-2020)
Publisher's website

Database for Arabic Speech Commands Recognition

Technology is all around us and it’s changing rapidly, expanding Internet access has had huge impacts on everyday lives as people do everything on their phones and computers. The widespread growth in the use of digital computers, have an increasing need to be able to communicate with machines in a simpler manner. One of the main tasks that can simplify communication with machines is speech recognition. In this work, we introduce the Arabic speech commands database that contains six Arabic control order words and Arabic spoken digits. The created database is used to analyze and compare the recognition accuracy and performance of three recognition techniques which are, Wavelet Time Scattering feature extraction with Support Vector Machine (SVM) classifier, Wavelet Time Scattering feature extraction with Long Short-Term Memory (LSTM) classifier, and Mel-Frequency Cepstrum Coefficients (MFCC) feature extraction with K-Nearest Neighbor (KNN) classifier. Finally, the experimental results show that the most accurate prediction of the database commands was 98.1250% given by Wavelet Time Scattering feature extraction and LSTM classifier and the fastest training time for the database was 144 minutes given by MFCC and KNN classifier. arabic 5 English 42
Osama A. Alkishriwo, Lina Tarek Benamer(12-2020)
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