<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>10</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Hichem Hafdaoui</style></author><author><style face="normal" font="default" size="100%">Mehadjebia, Cherifa</style></author><author><style face="normal" font="default" size="100%">Benatia, Djamel</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Using Probabilistic Neural Network (PNN) For Extracting Acoustic Microwaves (BAW) In Piezoelectric Material</style></title><secondary-title><style face="normal" font="default" size="100%"> International Conference in Artificial Intelligence in Renewable Energetic Systems (ICAIRES 2017)</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2017</style></year><pub-dates><date><style  face="normal" font="default" size="100%">2017</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://link.springer.com/chapter/10.1007/978-3-319-73192-6_32</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p style=&quot;text-align: justify;&quot;&gt;
	In this paper, we propose a new method for Bulk waves detection of an acoustic microwave signal during the propagation of acoustic microwaves in a piezoelectric substrate (Lithium Niobate LiNbO&lt;sub&gt;3&lt;/sub&gt;). We have used the classification by probabilistic neural network (PNN) as a means of numerical analysis in which we classify all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity in order to build a model from which we note the Bulk waves easily. These singularities inform us of presence of Bulk waves in piezoelectric materials.
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