Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...
—In this paper we face the following problem: how to provide each peer local access to the full information (not just a summary) that is distributed over all edges of an overlay ...
According to the recent theory of compressed sensing, accurate reconstruction is possible even from data samples dramatically smaller than Nyquist sampling limit as long as the un...
—Reliable wireless communications often requires accurate knowledge of the underlying multipath channel. This typically involves probing of the channel with a known training wave...
Waheed Uz Zaman Bajwa, Jarvis Haupt, Gil M. Raz, R...
Compressive-sensing cameras are an important new class of sensors that have different design constraints than standard cameras. Surprisingly, little work has explored the relation...