@article {6755,
	title = {Study of Leaky Acoustic Micro-Waves in Piezoelectric Material (Lithium Niobate Cut Y-X) Using Probabilistic Neural Network (PNN) Classification},
	journal = {INTERNATIONAL JOURNAL OF MICROWAVE AND OPTICAL TECHNOLOGY},
	volume = {17},
	number = {2},
	year = {2022},
	abstract = {In this paper, the leaky acoustic microwaves (LAW) in a piezoelectric substrate (Lithium Niobate LiNbO3 Cut Y-X) were studied. The main method for this research was classification using a probabilistic neural network (PNN).The originality of this method is in the accurate values it provides. In our case, this technique was helpful in identifying undetectable waves, which are difficult to identify by classical methods. Moreover, all the values of the real part and the imaginary part of the coefficient attenuation with the acoustic velocity were classified in order to build a model from which we could easily note the Leaky waves. Accurate values of the coefficient attenuation and acoustic velocity for Leaky waves were obtained. Hence, in this study, the focus was on the interesting modeling and realization of acoustic microwave devices (radiating structures) based on the propagation of acoustic microwaves},
	url = {https://www.researchgate.net/profile/Hichem-Hafdaoui/publication/359203934_Study_of_Leaky_Acoustic_Micro-Waves_in_Piezoelectric_Material_Lithium_Niobate_Cut_Y-X_Using_Probabilistic_Neural_Network_PNN_Classification/links/62318d304ba65b24813421f0/Study-of-},
	author = {Mechnane, Amel and Hichem Hafdaoui and Benatia, Djamel}
}
