4 citations · 8 across the 7 of their papers we have counts for
7 papers
Beam Steering by Two Vertically Faced Metasurfaces Using Polarization-Free Unit Cells with Three Operating Modes
Mohammadreza Jahangiri, Hossein Soleimani, Mohammad Soleimani
Intelligent reflecting surfaces (IRS) are valuable tools for enhancing the intelligence of the propagation environment. They have the ability to direct EM Waves to a specific user…
Deep Learning Framework for the Design of Orbital Angular Momentum Generators Enabled by Leaky-wave Holograms
Naser Omrani, Fardin Ghorbani, Sina Beyraghi +2
In this paper, we present a novel approach for the design of leaky-wave holographic antennas that generates OAM-carrying electromagnetic waves by combining Flat Optics (FO) and mac…
Simultaneous estimation of wall and object parameters in TWR using deep neural network
Fardin Ghorbani, Hossein Soleimani
This paper presents a deep learning model for simultaneously estimating target and wall parameters in Through-the-Wall Radar. In this work, we consider two modes: single-target and…
A deep learning approach for inverse design of the metasurface for dual-polarized waves
Fardin Ghorbani, Javad Shabanpour, Sina Beyraghi +3
Compared to the conventional metasurface design, machine learning-based methods have recently created an inspiring platform for an inverse realization of the metasurfaces. Here, we…
Through-the-Wall Radar under Electromagnetic Complex Wall: A Deep Learning Approach
Fardin Ghorbani, Hossein Soleimani
This paper employed deep learning to do two-dimensional, multi-target locating in Through-the-Wall Radar under conditions where the wall is treated as a complex electromagnetic med…
Deep neural network-based automatic metasurface design with a wide frequency range
Fardin Ghorbani, Sina Beyraghi, Javad Shabanpour +3
Beyond the scope of conventional metasurface which necessitates plenty of computational resources and time, an inverse design approach using machine learning algorithms promises an…
EEGsig: an open-source machine learning-based toolbox for EEG signal processing
Fardin Ghorbani, Javad Shabanpour, Sepideh Monjezi +3
In the quest to realize a comprehensive EEG signal processing framework, in this paper, we demonstrate a toolbox and graphic user interface, EEGsig, for the full process of EEG sig…