Polarization-versed calibration of spectrophotometric transducers

A new method for the calibration of spectrophotometric transducers is proposed. The method, using a radial-basis-function neural network, is designed to overcome two important drawbacks of existing methods, viz. their inability to deal with the problems implied by insufficiency of the number of output data, and light polarization. The results of a study of this method, based on semi-synthetic data, have been given, and conclusions, pointing out its practical usefulness, are drawn.