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A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition

A simplified correlation index is proposed to be used in real-time pulse shape recognition systems. This index is similar to the classic Pearson’s correlation coefficient, but it can be efficiently implemented in FPGA devices with far fewer logic resources and excellent performance. Numerical simula...

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Autores principales: Cicuttin, Andres, Morales, Iván René, Crespo, Maria Liz, Carrato, Sergio, García, Luis Guillermo, Molina, Romina Soledad, Valinoti, Bruno, Folla Kamdem, Jerome
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607046/
https://www.ncbi.nlm.nih.gov/pubmed/36298048
http://dx.doi.org/10.3390/s22207697
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author Cicuttin, Andres
Morales, Iván René
Crespo, Maria Liz
Carrato, Sergio
García, Luis Guillermo
Molina, Romina Soledad
Valinoti, Bruno
Folla Kamdem, Jerome
author_facet Cicuttin, Andres
Morales, Iván René
Crespo, Maria Liz
Carrato, Sergio
García, Luis Guillermo
Molina, Romina Soledad
Valinoti, Bruno
Folla Kamdem, Jerome
author_sort Cicuttin, Andres
collection PubMed
description A simplified correlation index is proposed to be used in real-time pulse shape recognition systems. This index is similar to the classic Pearson’s correlation coefficient, but it can be efficiently implemented in FPGA devices with far fewer logic resources and excellent performance. Numerical simulations with synthetic data and comparisons with the Pearson’s correlation show the suitability of the proposed index in applications such as the discrimination and counting of pulses with a predefined shape. Superior performance is evident in signal-to-noise ratio scenarios close to unity. FPGA implementation of Person’s method and the proposed correlation index have been successfully tested and the main results are summarized.
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spelling pubmed-96070462022-10-28 A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition Cicuttin, Andres Morales, Iván René Crespo, Maria Liz Carrato, Sergio García, Luis Guillermo Molina, Romina Soledad Valinoti, Bruno Folla Kamdem, Jerome Sensors (Basel) Article A simplified correlation index is proposed to be used in real-time pulse shape recognition systems. This index is similar to the classic Pearson’s correlation coefficient, but it can be efficiently implemented in FPGA devices with far fewer logic resources and excellent performance. Numerical simulations with synthetic data and comparisons with the Pearson’s correlation show the suitability of the proposed index in applications such as the discrimination and counting of pulses with a predefined shape. Superior performance is evident in signal-to-noise ratio scenarios close to unity. FPGA implementation of Person’s method and the proposed correlation index have been successfully tested and the main results are summarized. MDPI 2022-10-11 /pmc/articles/PMC9607046/ /pubmed/36298048 http://dx.doi.org/10.3390/s22207697 Text en © 2022 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 Article
Cicuttin, Andres
Morales, Iván René
Crespo, Maria Liz
Carrato, Sergio
García, Luis Guillermo
Molina, Romina Soledad
Valinoti, Bruno
Folla Kamdem, Jerome
A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition
title A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition
title_full A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition
title_fullStr A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition
title_full_unstemmed A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition
title_short A Simplified Correlation Index for Fast Real-Time Pulse Shape Recognition
title_sort simplified correlation index for fast real-time pulse shape recognition
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9607046/
https://www.ncbi.nlm.nih.gov/pubmed/36298048
http://dx.doi.org/10.3390/s22207697
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