Pan Pacific Symposium Conference Proceedings


Authors: Andrea Pirisi, et al.
Company: Politecnico di Milano, Dipartimento di Energia and Politecnico di Torino, Dipartimento di Elettronica
Date Published: 2/12/2009   Conference: Pan Pacific Symposium

Abstract: The growing attention of scientist to reflectarray antennas in recent years leads to develop effective ad-hoc ways to optimize antenna performances, often by means of evolutionary iterative algorithms. To enhance the speed of the optimization task, in this work a Neural Network model of an innovative printed radiating element is presented as convenient interface between antenna design and global optimization algorithms.

In particular, an artificial neural network (ANN) is proposed to predict the phase behaviour of a broadband patch radiator as a function of its geometric parameters. The characterization of the antenna is first obtained by numerical simulations, and the ANN is constructed to approximate the nonlinear relationship between the antenna geometry and the phase behaviour. Some preliminary results are provided to demonstrate the effectiveness of this method in providing a fast interface between the antenna model and the optimisation tool.

Key words: Printed antennas modeling, neural networks, evolutionary algorithms.

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