Fast L1-Minimization for Compressed Sensing Using Orthonormal Expansion

Keywords

acceleration accuracy accurate achieves acquisition additional alternatively augmented better brain cast champaign complementary compressed compressible computational computer conjugate constrained contains convergence convex core cost denote denotes depiction described details developed disk electrical electronic enables enforced engineering equipped equivalent error errors evaluated exhibit expanding expansion expense fast fixing form formulated formulation fully function gradient great hand highly holds implemented incurs info institute introduces involves iteration iterations iterative letting little manifest many matrix memory minimization minimized multiplier nominal nonlinear numerical ones onto operation operator optimally optimization orthonormal outline outlined partial pattern penalty performance phantom positive potential problem problems projecting proposed quadratic random real reconstructed reconstruction representation respectively root rows running sample sampled sampling scalar sensing significantly slow soft solution solved solves solving space sparse springer squares subject subset suffer tech term theory thresholding tractability transform underwent unitary vector whose written