Inertially controlled two-dimensional phased arrays by exploiting artificial neural networks and ultra-low-power AI-based microcontrollers

R Colella, L Spedicato, L Laqintana… - IEEE Access, 2023 - ieeexplore.ieee.org
The use of Artificial Intelligence (AI) in electronics and electromagnetics is opening many
attractive research opportunities related to the smart control of phased arrays. This is …

Source detection with multi-label classification

J Vijayamohanan, A Gupta… - IEEE Open Journal …, 2023 - ieeexplore.ieee.org
Radio source detection through conventional algorithms has been unreliable when trying to
solve for large number of sources in the presence of low SINR and less number of …

Detecting coherent sources with deep learning

J Vijayamohanan, A Gupta, S Goudos… - 2022 IEEE USNC …, 2022 - ieeexplore.ieee.org
Detecting correlated sources in a dynamic radio frequency (RF) environment is both
challenging and critical to antenna array processing. We introduce a deep learning …

Signal Detection with Machine Learning

J Vijayamohanan, A Gupta… - … for Future Networks, 2025 - Wiley Online Library
This chapter begins by delving into the signal detection problem and discusses the various
strategies for signal detection over a noisy channel. The generic detection framework is …

Convolutional neural networks for radio source detection

J Vijayamohanan, A Gupta… - … on Antennas and …, 2021 - ieeexplore.ieee.org
This paper introduces a Convolutional Neural Network (CNN) architecture for radio event
and source detection. The upper triangle of the auto-correlation matrix is extracted as the …

Source detection via multi-label classification

J Vijayamohanan, A Gupta, O Noakoasteen… - arxiv preprint arxiv …, 2022 - arxiv.org
Radio source detection through conventional algorithms has been unreliable when trying to
solve for large number of sources in the presence of low SINR and less number of …