CV


Mojtaba Hajiabadi

Mojtaba Hajiabadi

Assistant Professor

Faculty: Electrical and Computer Engineering

Department: Electronic

Degree: Ph.D

CV
Mojtaba Hajiabadi

Assistant Professor Mojtaba Hajiabadi

Faculty: Electrical and Computer Engineering - Department: Electronic Degree: Ph.D |

Dr. Mojtaba Hajiabadi, a graduate of Electrical Engineering with a focus on Telecommunication Systems, earned his Bachelor's degree in 2012 from the University of Birjand, his Master's degree in 2014, and his Ph.D. in 2018 from Ferdowsi University of Mashhad. He was an outstanding student, holding third rank in his Bachelor's, first in his Master's, and first in his Ph.D. In 2018, he completed a doctoral research opportunity at KU Leuven University in Belgium under the supervision of Professor Marc Moonen, a distinguished IEEE Fellow.

During his Ph.D., Dr. Hajiabadi received several awards from the National Elites Foundation, including research grants, teaching assistantships, and an international research opportunity grant. After completing his studies, he worked for five years in Iran's telecommunications industry, contributing to satellite communication transceivers in the aerospace sector and optical telecommunication systems at the Infrastructure Communications Company. Since 2022, he has been a full-time faculty member in the Communication Engineering Department, Faculty of Electrical and Computer Engineering, at the University of Birjand. His research interests include adaptive filters, machine learning, and AI in wireless communication systems.

If you are interested in collaborating on research in his field of expertise, you may contact him via the following email address:

Email: mhajiabadi@birjand.ac.ir

نمایش بیشتر

Exploring the potential of parallel adaptive filters for audio noise removal

AuthorsMojtaba Hajiabadi
JournalSignal, Image and Video Processing
Page number1-10
Serial number18
Volume number1
Paper TypeFull Paper
Published At2023
Journal TypeElectronic
Journal CountryIran, Islamic Republic Of
Journal IndexISI،JCR،Scopus

Abstract

This paper presents a novel adaptive structure for audio noise removal, aiming to enhance the performance of noise reduction. The proposed structure consists of a bank of parallel least-mean-squares, time-domain adaptive filters. Multiple microphones are employed to capture the noise source signal, while another microphone records the corrupted speech signal. By passing the recorded noise signals through the parallel adaptive filter bank structure and subtracting the results from the speech signal, the noise is effectively suppressed. Additionally, the noise removal performance is further improved by linearly combining the error signals, which include the noise-free speech signal. The effectiveness of the proposed adaptive structure is demonstrated through theoretical analysis and numerical simulations, highlighting its superior noise removal performance compared to traditional acoustic noise cancellation approaches.

Paper URL