A time domain reconstruction method of randomly sampled frequency sparse signal
In this paper stochastic sampling as a method of frequency sparse signal acquisition is presented. Basic principle of compressed sensing is reviewed, with emphasis on nonuniform sampling and signal reconstruction methods. A robust time domain reconstruction method of randomly sampled signal through...
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Veröffentlicht in: | Measurement : journal of the International Measurement Confederation 2018-10, Vol.127, p.68-77 |
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container_title | Measurement : journal of the International Measurement Confederation |
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creator | Andráš, Imrich Dolinský, Pavol Michaeli, Linus Šaliga, Ján |
description | In this paper stochastic sampling as a method of frequency sparse signal acquisition is presented. Basic principle of compressed sensing is reviewed, with emphasis on nonuniform sampling and signal reconstruction methods. A robust time domain reconstruction method of randomly sampled signal through compressed sensing approach is proposed. The presented reconstruction algorithm is evaluated by means of simulations, with comparison to conventional compressed sensing reconstruction and the most common practical issues taken into account. Simulation results indicate that the proposed reconstruction method is resistent to high levels of quantization and uncorrelated noise. Experiments with real hardware were also performed, results of which confirm the ability of stochastic sampling framework to overcome the Nyquist limit of analog-to-digital converters. |
doi_str_mv | 10.1016/j.measurement.2018.05.065 |
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Experiments with real hardware were also performed, results of which confirm the ability of stochastic sampling framework to overcome the Nyquist limit of analog-to-digital converters.</description><subject>Algorithms</subject><subject>Analog to digital conversion</subject><subject>Analog to digital converters</subject><subject>Analog-to-information conversion</subject><subject>Compressed sensing</subject><subject>Computer simulation</subject><subject>Detection</subject><subject>Experiments</subject><subject>Measurement</subject><subject>Nonuniform sampling</subject><subject>Random sampling</subject><subject>Sampling</subject><subject>Signal reconstruction</subject><subject>Simulation</subject><subject>Sparse signal</subject><subject>Stochastic models</subject><subject>Stochastic sampling</subject><subject>Time domain analysis</subject><issn>0263-2241</issn><issn>1873-412X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2018</creationdate><recordtype>article</recordtype><recordid>eNqNkE9LAzEUxIMoWKvfIeJ517ykm22OpfgPCr0oeAvZ7Itm6W7WZCv025tSDx49PXjMDDM_Qm6BlcBA3ndljybtI_Y4TCVnsCxZVTJZnZEZLGtRLIC_n5MZ41IUnC_gklyl1DHGpFByRrYrOvkeaRt64wca0YYhTXFvJx8G2uP0GVoaHI1myJLdgSbTjztsqYv4tcfB5s9oYkKa_MdgdtfkwpldwpvfOydvjw-v6-dis316Wa82hRULNRUNOlDGKuGkrFsLQvAGzbJG6aSrnICat6biAppKKVGhQAUCoK4Ncw3WVszJ3Sl3jCH3SJPuwj7mAklzgOxRUtRZpU4qG0NKEZ0eo-9NPGhg-shPd_oPP33kp1mlM7_sXZ-8mGd8e4w6WZ8HY-szpUm3wf8j5Qc9zIDO</recordid><startdate>201810</startdate><enddate>201810</enddate><creator>Andráš, Imrich</creator><creator>Dolinský, Pavol</creator><creator>Michaeli, Linus</creator><creator>Šaliga, Ján</creator><general>Elsevier Ltd</general><general>Elsevier Science Ltd</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>201810</creationdate><title>A time domain reconstruction method of randomly sampled frequency sparse signal</title><author>Andráš, Imrich ; Dolinský, Pavol ; Michaeli, Linus ; Šaliga, Ján</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c349t-bef19ac93f667dc1332bea87e6f6f5f3172da5231b59935e3e9131177a0fbe7c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2018</creationdate><topic>Algorithms</topic><topic>Analog to digital conversion</topic><topic>Analog to digital converters</topic><topic>Analog-to-information conversion</topic><topic>Compressed sensing</topic><topic>Computer simulation</topic><topic>Detection</topic><topic>Experiments</topic><topic>Measurement</topic><topic>Nonuniform sampling</topic><topic>Random sampling</topic><topic>Sampling</topic><topic>Signal reconstruction</topic><topic>Simulation</topic><topic>Sparse signal</topic><topic>Stochastic models</topic><topic>Stochastic sampling</topic><topic>Time domain analysis</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Andráš, Imrich</creatorcontrib><creatorcontrib>Dolinský, Pavol</creatorcontrib><creatorcontrib>Michaeli, Linus</creatorcontrib><creatorcontrib>Šaliga, Ján</creatorcontrib><collection>CrossRef</collection><jtitle>Measurement : journal of the International Measurement Confederation</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Andráš, Imrich</au><au>Dolinský, Pavol</au><au>Michaeli, Linus</au><au>Šaliga, Ján</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A time domain reconstruction method of randomly sampled frequency sparse signal</atitle><jtitle>Measurement : journal of the International Measurement Confederation</jtitle><date>2018-10</date><risdate>2018</risdate><volume>127</volume><spage>68</spage><epage>77</epage><pages>68-77</pages><issn>0263-2241</issn><eissn>1873-412X</eissn><abstract>In this paper stochastic sampling as a method of frequency sparse signal acquisition is presented. 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subjects | Algorithms Analog to digital conversion Analog to digital converters Analog-to-information conversion Compressed sensing Computer simulation Detection Experiments Measurement Nonuniform sampling Random sampling Sampling Signal reconstruction Simulation Sparse signal Stochastic models Stochastic sampling Time domain analysis |
title | A time domain reconstruction method of randomly sampled frequency sparse signal |
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