of the Dissertation A Scalable VLSI Architecture for Real-Time and Energy-Efficient Sparse Approximation in Compressive Sensing Systems

An Efficient Algorithm For Total Variation Regularization with Applications to the Single Pixel Camera and Compressive Sensing

Although wireless sensor networks are considered as one of the prominent solutions for flood monitoring, energy constraint nature sensors is still a technical challenge. In this letter, we tackle problem by proposing novel energy-efficient remote monitoring system, enabled compressive sensing. The proposed approach compressively captures water level data using i) random block-based sampler, and...

approved: Bechir Hamdaoui This thesis proposes a novel technique that exploits spectrum occupancy behaviors inherent to wideband spectrum access to enable efficient cooperative spectrum sensing. The proposed technique reduces the number of required sensing measurements while accurately recovering spectrum occupancy information. It does so by leveraging compressive sampling theory to exploit the...

We present our latest results in static compressive tracking and imaging. We have developed a design methodology using the compressed sensing concept of mutual coherence. We also elucidate a modified calibration scheme that boosts compressive imaging capabilities. © 2012 Optical Society of America OCIS codes: (110.1758) Computational imaging; (100.4999) Pattern recognition, target tracking