Solving inverse problems in applied spectroscopy with random fractal noise

Abstract

In the framework of the statistical regularization method new algorithms of solving inverse problems in applied spectroscopy in the presence of correlated fractal noises are suggested. Statistical properties of fractal noises are investigated in terms of R/S-analysis. As an example illustrating the efficiency of the algorithms suggested the smoothing problem of experimental data is considered. (C) 2000 Elsevier Science Ltd. All rights reserved. | In the framework of the statistical regularization method new algorithms of solving inverse problems in applied spectroscopy in the presence of correlated fractal noises are suggested. Statistical properties of fractal noises are investigated in terms of R/S-analysis. As an example illustrating the efficiency of the algorithms suggested the smoothing problem of experimental data is considered.