Abstract
Neural Networks are relevant statistical methods to extract information from data when physical phenomena are very complicated and cannot be described in terms of theoretical analysis. Scatterometers are active microwave radar which accurately measure the power of the backscatter signal versus incident signal in order to calculate the normalized radar cross section ( σ 0) of the ocean surface. We use multilayer perceptrons in order to determine the Geophysical Model Function and to estimate the variability of the signal of ERS-1, ERS-2 and NSCAT scatterometers.
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