PROJECT TITLE :Uniform Recovery Bounds for Structured Random Matrices in Corrupted Compressed Sensing - 2018ABSTRACT:We study the problem of recovering an s-sparse signal x* ? C n from corrupted measurements y = Ax* + z* + w,
PROJECT TITLE :Recovery of Structured Signals With Prior Information via Maximizing Correlation - 2018ABSTRACT:This Project considers the problem of recovering a structured signal from a relatively small number of noisy measurements
PROJECT TITLE :Quantized Spectral Compressed Sensing: Cramer–Rao Bounds and Recovery Algorithms - 2018ABSTRACT:Efficient estimation of wideband spectrum is of nice importance for applications like cognitive radio. Recently,
PROJECT TITLE :Low-Rank Matrix Recovery From Noisy, Quantized, and Erroneous Measurements - 2018ABSTRACT:This Project proposes a communication-reduced, cyber-resilient, and data-preserved data collection framework. Random noise
PROJECT TITLE :Accurate Recovery of Internet Traffic Data Under Variable Rate Measurements - 2018ABSTRACT:The inference of the network traffic matrix from partial measurement information becomes increasingly vital for various

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