engleski

The Use of Information Entropy in Extracting the Irregularities of Autonomous Systems

Information system is of considerable importance in preserving the predicted functioning of diverse systems, such as autonomous robotic systems. Its dynamics is in many cases highly nontrivial with a finite probability of errors caused by nontrivially interfering causes. It is, therefore, of importance to predict possible errors, configure the system so that it can function, at least partially, with these errors and altogether validate it. Among the variety of types of errors, in this article we concentrate on errors of gradual and distributed rise. We utilise the information entropy approach to extract the errors during the phase of their gradual rise. Algorithm is given for attributing the information entropy to the part of information system and for using it to extract irregularities in predicted dynamics of information system and overall of the autonomous robotic system.

automatic robotic system; error development; information entropy

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