Mathematical models for the improvement of detection techniques of industrial noise sources from acoustic images-Reference-Cited by-同舟云学术

Mathematical models for the improvement of detection techniques of industrial noise sources from acoustic images

Published:2021-05-04 Issue:13 Volume:44 Page:10448-10459
ISSN:0170-4214
Container-title:Mathematical Methods in the Applied Sciences
language:en
Short-container-title:Math Meth Appl Sci

Author:

Asdrubali Francesco¹^ORCID,Baldinelli Giorgio²^ORCID,Bianchi Francesco³,Costarelli Danilo⁴^ORCID,D'Alessandro Francesco⁵^ORCID,Scrucca Flavio⁶^ORCID,Seracini Marco⁴^ORCID,Vinti Gianluca⁴^ORCID

Affiliation:

1. Department of Engineering University of Roma Tre Roma Italy

2. Department of Engineering University of Perugia Perugia Italy

3. Department of Physics and Geology University of Perugia Perugia Italy

4. Department of Mathematics and Computer Science University of Perugia Perugia Italy

5. Institute on Atmospheric Pollution at Italian Ministry of Environment, Land and Sea Italian National Research Council Rome Italy

6. Department of Sustainability, Circular Economy Section ENEA, Italian National Agency for New Technologies Energy and Sustainable Economic Development Rome Italy

Funder

Fondazione Cassa di Risparmio di Perugia

Publisher

Wiley

Subject

General Engineering,General Mathematics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mma.7420

Reference36 articles.

1. AsdrubaliF BaldinelliG BianchiF et al.Innovative techniques for the improvement of industrial noise sources identification by beamforming. submitted;2020.

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3. A comparison between the sampling Kantorovich algorithm for digital image processing with some interpolation and quasi-interpolation methods

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5. Detection of thermal bridges from thermographic images by means of image processing approximation algorithms

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