Tomislav Gajić

Applications of probabilistic model based on main quantum mechanics concepts

Recently, the several applications of the probabilistic model based on two of the main concepts in quantum physics - a density matrix and the Born rule, have been introduced. It was shown that the model can be suitable for the modeling of learning algorithms in biologically plausible artificial neural networks framework, like it is the case of on-line learning algorithms for Independent /Principal/Minor Component Analysis, which could be realized on parallel hardware based on very simple computational units. Also, it has been shown that the quantum entropy of the system, related to that model, can be successfully used in the problems like change point detection, with some examples of applications in the area of power electronics and general classification problems. Here, we present a robust on-line Principal Component Algorithm based on the proposed model, which extracts several principal components simultaneously. Also, we will show usefulness of the proposed method in a simple example of image segmentation.

Joint excitation and reactive power control in thermal power plant

The coordinated voltage and reactive power controller, designed for the thermal power plant, is presented in the paper. A brief explanation of the need for such device is given and justification for commissioning of such equipment is outlined. After short description of the theoretical background of the proposed control design, the achieved features of the commissioned equipment are fully given. Achieved performances are illustrated by recorded reactive power and bus voltage responses after commissioning of the described equipment into the largest thermal power plant in Serbia. As it can be seen in presented records, all design targets are met.