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All Journal Bulletin of Electrical Engineering and Informatics
Mohammad Arif Sobhan Bhuiyan
Xiamen University Malaysia
Electrical & Electronics Engineering

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Design of a low-power compact CMOS variable gain amplifier for modern RF receivers M. J. Alam; Mohammad Arif Sobhan Bhuiyan; Md Torikul Islam Badal; Mamun Bin Ibne Reaz; Noorfazila Kamal
Bulletin of Electrical Engineering and Informatics Vol 9, No 1: February 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (470.963 KB) | DOI: 10.11591/eei.v9i1.1468

Abstract

The demand for portability has speeded up the design of low-power electronic communication devices. Variable gain amplifier (VGA) is one of the most vulnerable elements of every modern receiver for the proper baseband processing of the signal. CMOS VGAs are generally suffered from low bandwidth and small gain range. In this research, a two-stage class AB VGA, each stage comprising of a direct transconductance amplifier and a linear transimpedance amplifier, is designed in Silterra 0.13-μm CMOS utilizing Mentor Graphics environment. The post-layout simulation results reveal that the VGA design achieves the widest bandwidth of more than 200 MHz and high gain range from -33 to 32 dB. The VGA dissipates only 2mW from a single 1.2 V DC supply. The core chip area of the VGA is also only 0.026 mm2 which is also the lowest compared to recent researches. Such a VGA will be a very useful module for all modern communication devices.
Advanced real-time face detection and recognition in MATLAB Walid El Fezzani; Mahdi H. Miraz; Mohammad Arif Sobhan Bhuiyan
Bulletin of Electrical Engineering and Informatics Vol 15, No 2: April 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/eei.v15i2.9431

Abstract

Face detection and recognition technologies are increasingly vital in security and surveillance. This article covers two main areas with real-time application: the basics of image processing, such as edge detection and filters, and an overview of global methods for face detection and recognition. The Viola-Jones algorithm, based on Haar-like features and a cascade of classifiers, has been utilized for detecting objects within the images. MATLAB’s toolbox has been used to further enhance face detection performance by identifying human facial patterns in webcam-captured frames. For face recognition, the algorithm compares a detected face with reference images, counting zero-valued differences. If these zero elements exceed a certain threshold, a match is confirmed, indicating a high similarity between the captured face and the reference image. This study presents a low-cost MATLAB prototype emphasizing practical, educational demonstration of real-time face analysis.
Co-Authors M. J. Alam Mahdi H. Miraz Mamun Bin Ibne Reaz Md Torikul Islam Badal Noorfazila Kamal Walid El Fezzani