Inversion of turbidity measurements of polymer latex using wavelet functions

The determination of the particle size distribution (PSD) of latex from turbidimetry at several wavelength may be considered as an inverse problem. Classical regularization methods to solve ill conditioned linear inverse problems have been applied to this problem previously. Poor quality results were obtained when the range of the particle sizes is wide and the particles are small. The wavelet-based approach investigated in this work considers the expansion of the solution in wavelet series with selective regularization of each component of the expansion. The results achieved from simulated experiments show that the solutions obtained by classical regularization methods can be improved by means of wavelet-based regularization. The method is developed so that good initial values for the regularization parameters can be selected using different techniques.