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03/13/2022
One-Bit Compressive Sensing: Can We Go Deep and Blind?
One-bit compressive sensing is concerned with the accurate recovery of a...
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02/05/2021
LoRD-Net: Unfolded Deep Detection Network with Low-Resolution Receivers
The need to recover high-dimensional signals from their noisy low-resolu...
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12/21/2020
Unfolded Algorithms for Deep Phase Retrieval
Exploring the idea of phase retrieval has been intriguing researchers fo...
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11/15/2020
Deep-RLS: A Model-Inspired Deep Learning Approach to Nonlinear PCA
In this work, we consider the application of model-based deep learning i...
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03/09/2020
UPR: A Model-Driven Architecture for Deep Phase Retrieval
The problem of phase retrieval has been intriguing researchers for decad...
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02/03/2020
Deep-URL: A Model-Aware Approach To Blind Deconvolution Based On Deep Unfolded Richardson-Lucy Network
The lack of interpretability in current deep learning models causes seri...
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12/17/2019
Deep Radar Waveform Design for Efficient Automotive Radar Sensing
In radar systems, unimodular (or constant-modulus) waveform design plays...
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12/10/2019
Deep One-bit Compressive Autoencoding
Parameterized mathematical models play a central role in understanding a...
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11/27/2019
Model-Aware Deep Architectures for One-Bit Compressive Variational Autoencoding
Parameterized mathematical models play a central role in understanding a...
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08/01/2019
Optimized Transmission for Parameter Estimation in Wireless Sensor Networks
A central problem in analog wireless sensor networks is to design the ga...
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12/10/2018
Signal Recovery From 1-Bit Quantized Noisy Samples via Adaptive Thresholding
In this paper, we consider the problem of signal recovery from 1-bit noi...
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11/30/2018
