We introduce numerical methods and algorithms to estimate the main parameters of fractal-like particle aggregates from their optical structure factor (i.e. light scattering diagrams). The first algorithm is based on a direct and simple method, but its applicability is limited to aggregates with large size parameter and intermediate fractal dimension. The second algorithm requires to build calibration curves based on accurate particle agglomeration and particle light scattering models. It allows analyzing the optical structure factor of much smaller aggregates, regardless of their fractal dimension and the size of the single particles. Therefore, this algorithm as well as the introduction of a criterial curve to detect the different scattering regimes, are thought to be powerful tools to perform reliable and reproducible analysis.

The wavelet transform has been successfully used in the area of power quality analysis. There are many published papers with methods for power quality disturbance classification or harmonics measurement, which use wavelet transform. However, the properties of the wavelet transform can drastically vary from the choice of the wavelet. In this paper we analyze the influence of the choice of the wavelet to the accuracy of the power quality classification method and to high frequency harmonics measurements. Additionally to the well known wavelet filters we introduce near perfect reconstruction filter banks. The simulation results indicate that these filter banks are a good choice for classification of power quality disturbances, especially in the presence of noise and for high frequency harmonics measurements