Neural Networks to Retrieve Seismic Source Parameters by Sar Interferometry

Details Neural Networks to Retrieve Seismic Source Parameters by Sar Interferometry Neural Networks to Retrieve Seismic Source Parameters by Sar Interferometry

Jun 2004

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2004esasp.550e..79d&link_type=abstract

Proceedings of the FRINGE 2003 Workshop (ESA SP-550). 1-5 December 2003, ESA/ESRIN, Frascati, Italy. Editor: H. Lacoste. Publish

Computer Science

Learning

Scientific paper

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.

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