Azhar Niaz

Work place: Department of Electrical and Electronic Engineering, Ahsanullah University of Science & Technology, Dhaka-1208, Bangladesh

E-mail: azharniazkakon@gmail.com

Website:

Research Interests: Speech Synthesis, Speech Recognition, Image and Sound Processing, Communications

Biography

AZHAR NIAZ received his B.Sc (Hons) majoring in Electrical and Electronic from Ahsanullah University of Science and Technology in 2018. His research interests include Speech processing, communications, and Electronics.

Author Articles
BER Performance Optimization of the SFBC-OFDM System for Economical Receiver Design with Imperfect Channel Estimation

By Md. Jakaria Rahimi Md. Shaikh Abrar Kabir Azhar Niaz Md. Jahidul Islam Oli Lowna Baroi

DOI: https://doi.org/10.5815/ijwmt.2019.06.03, Pub. Date: 8 Nov. 2019

In this paper, the bit error rate (BER) performance of SFBC-OFDM systems for frequency selective fading channels is observed for various antenna orientations and modulation schemes. The objective is to find out a suitable configuration with minimum number of receiving antenna that requires minimum signal power level at the receiver to provide reliable voice and video communication. We have considered both M-ary phase shift keying (MPSK) and M-ary quadrature amplitude modulation (MQAM) in the performance analysis considering both perfect and imperfect channel state information (CSI). The authors have expressed the BER under imperfect channel estimation condition as a function of BER under perfect channel condition in this paper. The finding shows, for a BTS with 4 transmitting antenna and MS with 2 receiving antenna BPSK performs better for both perfect and imperfect CSI. Maximum permissible channel estimation error increases with the usage of more receiving antenna at the expense of increased cost.

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Effects of Filter Numbers and Sampling Frequencies on the Performance of MFCC and PLP based Bangla Isolated Word Recognition System

By Oli Lowna Baroi Md. Shaikh Abrar Kabir Azhar Niaz Md. Jahidul Islam Md. Jakaria Rahimi

DOI: https://doi.org/10.5815/ijigsp.2019.11.05, Pub. Date: 8 Nov. 2019

In this work, a 5 state left to right HMM-based Bangla Isolated word speech recognizer has been developed. To train and test the recognizer, a small corpus of various sampling frequencies have been developed in noisy as well as the noiseless environment. The number of filter banks is varied during the feature extraction phase for both MFCC and PLP. The effects of 2nd and 3rd differential coef´Čücients have also been observed. Experimental results exhibit that MFCC based feature extraction technique is better in CLASSROOM environment on the contrary PLP based technique performs better not only in a noiseless environment but also in when AC or FAN noise is present. We have also noticed that higher sampling frequency and higher filter order don’t always help to improve the performance.

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Agent-Based Buyer-Trader Interaction Model of Traditional Markets

By Purba D. Kusuma Azhar Niaz Reza Pulungan

DOI: https://doi.org/10.5815/ijisa.2016.11.01, Pub. Date: 8 Nov. 2016

One problem in simulating crowds in traditional markets is calculating the interaction duration between traders and buyers. This problem can be solved in a simple way by doing field observation to obtain some samples to find the average interaction duration between traders and buyers. This method is simple. On the other hand, the result will be less valid if the parameters are change. The purpose of this research is to develop an interaction model between traders and buyers by looking deeper into the negotiation process. This model is developed based on multi-agent system. Output of this model is the interaction duration. This model has been implemented in a traditional market crowd simulation. Based on the simulation, by adjusting the parameters in this model, the interaction duration by the model matches the real condition in traditional markets.

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Other Articles