JW Choi, B Shim, Y Ding, B Rao… - … Surveys & Tutorials, 2017 - ieeexplore.ieee.org
As a paradigm to recover the sparse signal from a small set of linear measurements, compressed sensing (CS) has stimulated a great deal of interest in recent years. In order to …
J Lee, GT Gil, YH Lee - IEEE Transactions on Communications, 2016 - ieeexplore.ieee.org
We propose an efficient open-loop channel estimator for a millimeter-wave (mm-wave) hybrid multiple-input multiple-output (MIMO) system consisting of radio-frequency (RF) …
This first chapter formulates the objectives of compressive sensing. It introduces the standard compressive problem studied throughout the book and reveals its ubiquity in many …
Compressed sensing is an exciting, rapidly growing field, attracting considerable attention in electrical engineering, applied mathematics, statistics and computer science. This book …
This paper presents a new approach to single-image superresolution, based upon sparse signal representation. Research on image statistics suggests that image patches can be well …
J Wright, AY Yang, A Ganesh… - IEEE transactions on …, 2008 - ieeexplore.ieee.org
We consider the problem of automatically recognizing human faces from frontal views with varying expression and illumination, as well as occlusion and disguise. We cast the …
D Jiang, W Wang, L Shi, H Song - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Estimation of end-to-end network traffic plays an important role in traffic engineering and network planning. The direct measurement of a network's traffic matrix consumes large …
This article presents novel results concerning the recovery of signals from undersampled data in the common situation where such signals are not sparse in an orthonormal basis or …