Open AccessStepwise fuzzy correction of the algorithm filters of random signals
Author(s) -
А. А. Лобатый,
А. С. Радкевич
Publication year - 2019
Publication title -
sistemnyj analiz i prikladnaâ informatika
Language(s) - English
Resource type - Journals
eISSN - 2414-0481
pISSN - 2309-4923
DOI - 10.21122/2309-4923-2019-1-35-40
Subject(s) - normalization (sociology) , algorithm , fuzzy logic , kalman filter , a priori and a posteriori , mathematics , filter (signal processing) , computer science , artificial intelligence , statistics , computer vision , philosophy , epistemology , sociology , anthropology
The task of estimating the information contained in random signals from various sources – meters. It is assumed that the gauges are discrete and are described, like the original process assessed, by a discrete mathematical model in the form of difference equations. As an estimation algorithm, we consider a discrete Kalman filter, which, in the general case, when mathematical models are inadequate to real processes, can give distorted information. To improve the accuracy of estimation, it is proposed to apply the integration of all possible meters with the introduction of additional a priori information using a fuzzy logic system. At the same time, it is proposed to make a transition from the obtained probability characteristics of the estimated process to the membership functions of fuzzy logic based on the output filter parameters using the normalization of the posterior probability density. This approach allows to increase the accuracy of estimation, as it takes into account additional information and its complex processing.