225 citations · 888 across the 36 of their papers we have counts for
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Unfolded Algorithms for Deep Phase Retrieval
Naveed Naimipour, Shahin Khobahi, Mojtaba Soltanalian
Exploring the idea of phase retrieval has been intriguing researchers for decades, due to its appearance in a wide range of applications. The task of a phase retrieval algorithm is…
On the Performance of One-Bit DoA Estimation via Sparse Linear Arrays
Saeid Sedighi, M. R. Bhavani Shankar, Mojtaba Soltanalian +1
Direction of Arrival (DoA) estimation using Sparse Linear Arrays (SLAs) has recently gained considerable attention in array processing thanks to their capability to provide enhance…
Deep-RLS: A Model-Inspired Deep Learning Approach to Nonlinear PCA
Zahra Esmaeilbeig, Shahin Khobahi, Mojtaba Soltanalian
In this work, we consider the application of model-based deep learning in nonlinear principal component analysis (PCA). Inspired by the deep unfolding methodology, we propose a tas…
UPR: A Model-Driven Architecture for Deep Phase Retrieval
Naveed Naimipour, Shahin Khobahi, Mojtaba Soltanalian
The problem of phase retrieval has been intriguing researchers for decades due to its appearance in a wide range of applications. The task of a phase retrieval algorithm is typical…
Efficient Waveform Covariance Matrix Design and Antenna Selection for MIMO Radar
Arindam Bose, Shahin Khobahi, Mojtaba Soltanalian
Controlling the radar beam-pattern by optimizing the transmit covariance matrix is a well-established approach for performance enhancement in multiple-input-multiple-output (MIMO)…
Deep-URL: A Model-Aware Approach To Blind Deconvolution Based On Deep Unfolded Richardson-Lucy Network
Chirag Agarwal, Shahin Khobahi, Arindam Bose +2
The lack of interpretability in current deep learning models causes serious concerns as they are extensively used for various life-critical applications. Hence, it is of paramount…