We propose and analyze an extremely fast, efficient and simple method for solving the problem: min{ u 1 :Au=f,u∈Rn }. This method was first described in [1], with more details i...
This paper develops theoretical results regarding noisy 1-bit compressed sensing and sparse binomial regression. We demonstrate that a single convex program gives an accurate estim...
Compressed sensing (CS) has recently emerged as a powerful signal acquisition paradigm. In essence, CS enables the recovery of high-dimensional sparse signals from relatively few ...
Jarvis Haupt, Waheed Uz Zaman Bajwa, Gil M. Raz, R...
Without reconstructing the signal themselves, signal detection could be solved by detection algorithm, which directly processes sampling value obtained from compressive sensing si...
Compressive sensing (CS) has been proposed for signals with sparsity in a linear transform domain. We explore a signal dependent unknown linear transform, namely the impulse respo...