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Obstacle modeling in array synthesis using neural networks

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2 Author(s)
Ayestaran, R.G. ; Univ. de Oviedo, Gijon ; Las-Heras, F.

A new neural network-based method able to perform synthesis over real radiating structures in presence of obstacles is presented. The method is based on the ability of neural networks to establish a relation between inputs and outputs from a previous training procedure with known sets of pairs input/output. If such sets are obtained using a full-waveform analysis tool, a neural network can estimate the voltages that must be applied to the radiating elements of an array in order to get a desired radiated field distribution, taking into account interactions between elements and the presence of obstacles in a near environment

Published in:

Antennas and Propagation, IEEE Transactions on  (Volume:54 ,  Issue: 8 )

Date of Publication:

Aug. 2006

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