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Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation

Data acquisition systems have shown the need of wideband spectrum monitoring for many years. This paper describes and discusses a recently proposed architecture aimed at acquiring efficiently wideband signals, named the Analog-to-Information Converter (AIC). AIC framework and working principle imple...

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Autores principales: Iadarola, Grazia, Daponte, Pasquale, De Vito, Luca, Rapuano, Sergio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863968/
https://www.ncbi.nlm.nih.gov/pubmed/36679659
http://dx.doi.org/10.3390/s23020861
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author Iadarola, Grazia
Daponte, Pasquale
De Vito, Luca
Rapuano, Sergio
author_facet Iadarola, Grazia
Daponte, Pasquale
De Vito, Luca
Rapuano, Sergio
author_sort Iadarola, Grazia
collection PubMed
description Data acquisition systems have shown the need of wideband spectrum monitoring for many years. This paper describes and discusses a recently proposed architecture aimed at acquiring efficiently wideband signals, named the Analog-to-Information Converter (AIC). AIC framework and working principle implementing the sub-Nyquist sampling are analyzed in general terms. Attention is specifically focused on the idea of exploiting the condition of the signals that, despite their large bandwidth, have a small information content in the frequency domain. However, as clarified in the paper, employing AICs in measurement instrumentation necessarily entails their characterization, through the analysis of their building blocks and the corresponding non-idealities, in order to improve the signal reconstruction.
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spelling pubmed-98639682023-01-22 Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation Iadarola, Grazia Daponte, Pasquale De Vito, Luca Rapuano, Sergio Sensors (Basel) Perspective Data acquisition systems have shown the need of wideband spectrum monitoring for many years. This paper describes and discusses a recently proposed architecture aimed at acquiring efficiently wideband signals, named the Analog-to-Information Converter (AIC). AIC framework and working principle implementing the sub-Nyquist sampling are analyzed in general terms. Attention is specifically focused on the idea of exploiting the condition of the signals that, despite their large bandwidth, have a small information content in the frequency domain. However, as clarified in the paper, employing AICs in measurement instrumentation necessarily entails their characterization, through the analysis of their building blocks and the corresponding non-idealities, in order to improve the signal reconstruction. MDPI 2023-01-11 /pmc/articles/PMC9863968/ /pubmed/36679659 http://dx.doi.org/10.3390/s23020861 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Perspective
Iadarola, Grazia
Daponte, Pasquale
De Vito, Luca
Rapuano, Sergio
Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation
title Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation
title_full Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation
title_fullStr Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation
title_full_unstemmed Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation
title_short Over the Limits of Traditional Sampling: Advantages and Issues of AICs for Measurement Instrumentation
title_sort over the limits of traditional sampling: advantages and issues of aics for measurement instrumentation
topic Perspective
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9863968/
https://www.ncbi.nlm.nih.gov/pubmed/36679659
http://dx.doi.org/10.3390/s23020861
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