Comparative between (LiNbO3) and (LiTaO3) in detecting acoustics microwaves using classification

Hafdaoui Hichem (University of Batna 2 (Mostefa Benboulaid))
Benatia Djamel (University of Batna 2 (Mostefa Benboulaid))

IAES International Journal of Artificial Intelligence (IJ-AI)
Vol 8, No 1: March 2019

Our work is mainly about detecting acoustics microwaves in the type of BAW (Bulk acoustic waves), where we compared between Lithium Niobate (LiNbO3) and Lithium Tantalate (LiTaO3), during the propagation of acoustic microwaves in a piezoelectric substrate. In this paper, 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 for conclude whichever is the best in utilization for generating bulk acoustic waves.This study will be very interesting in modeling and realization of acoustic microwaves devices (ultrasound) based on the propagation of acoustic microwaves.