The application of one-bit sampling technology in synthetic aperture radar (SAR) systems
has great potential due to its attractive advantages such as fast sampling speed, low data …

Parameterized mathematical models play a central role in understanding and design of
complex information systems. However, they often cannot take into account the intricate …

This paper proposes a federated learning technique for deep algorithm unfolding with
applications to sparse signal recovery and compressed sensing. We refer to this architecture …

Prediction of the temperature history of printed paths in additive manufacturing is crucial
towards establishing the process-structure-property relationship. Traditional approaches for …

In this thesis we lay the foundations of model-based deep learning with applications in
various signal processing fields such as communication systems, compressive sensing …