Compressive sensing and sub-Nyquist sampling
Roi Arie, Avraham Brand, Shlomo Engelberg
Abstract
The Nyquist-Shannon sampling theorem states that if all that you know about a signal is that its highest frequency is no greater than B, then if you want to sample the signal without any loss of information, you must sample it at a rate that is greater than 2B. If we call the rate at which we sample Fs, then we find that B <; Fs/2, and Fs/2 is called the Nyquist frequency. For a simple proof of the necessity of the condition B <; Fs/2, please see Sidebar: The Necessity of the Condition B <; Fs/2.
Topics & Concepts
Nyquist–Shannon sampling theoremNyquist rateSIGNAL (programming language)Nyquist frequencySampling (signal processing)Compressed sensingSample (material)MathematicsAnti-aliasing filterComputer scienceStatisticsTelecommunicationsControl theory (sociology)AlgorithmPhysicsMathematical analysisBandwidth (computing)Artificial intelligenceDetectorRoot-raised-cosine filterDigital filterThermodynamicsProgramming languageControl (management)Sparse and Compressive Sensing TechniquesMicrowave Imaging and Scattering AnalysisDistributed Sensor Networks and Detection Algorithms