With the increasing utilization of multi-spectral imaging sensors, automatic identification of spectral signatures would be an invaluable facility. Conventional, linear approaches have been shown to be limited: although reasonably stable in the presence of small amounts of noise, their performance degrades severelyat high noise levelsor when several spectra are combined. Nonlinear approaches are therefore attractive.
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