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NEURAL NETWORKS TO RETRIEVE SEISMIC SOURCE PARAMETERS BY SAR INTERFEROMETRY

The use of supervised neural networks for the estimation of seismic source parameters from SAR interferometric data is presented in this paper. The RNGCHN software allowed the generation of the input-output pairs necessary for the learning phase of the net. After being trained, the net has been tested on real measured data. The obtained results encourage future developments of such an approach.