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Accurate neural model identification of measurement devices |
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| Authors: | Andrea Bernieri Pasquale Daponte Domenico Grimaldi |
| Affiliation: | a Dip. di Ingeegneria Industriale, Università di Cassino, Via G. Di Biasio 43, I-03043, Cassino, (FR, Italy b Dip. di Ingegneria dell'Informazione ed Ingegneria Elettrica, Università di Salerno, I-84084, Fisciano, (SA, Italy c Dip. di Elettronica, Informatica e Sistemistica, Università della Calabria, I-87036, Rende, (CS, Italy |
| Abstract: | A neural approach to modeling measurement devices is presented. This approach allows the usual components of a measurement apparatus (transducers, filters, amplifiers, analog-to-digital converters, etc.) to be easily modeled by means of suitably trained artificial neural networks. Two applications regarding analog and mixed analog/digital devices are reported, highlighting the peculiarity of this approach and the accuracy that can be obtained. |
| Keywords: | System modeling Measurement devices Artificial Neural networks |
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