NDLI: An algorithm for identification and computer visualization of events I

Content Provider	Springer Nature Link
Author	Mal’kov, K. V. Tunitsky, D. V.
Copyright Year	2009
Abstract	A constructive algorithm for processing and identifying events of arbitrary nature is proposed. Ideologically, this algorithm is based on combination of two known approaches: fuzzy sets theory (the fact that the event is “typical” or “untypical” is determined by the value of its membership degree) and the method of potential functions (the metric properties of events are determined with the help of a symmetric nonnegative kernel given by one or another method). From the theoretical point of view, this is an adaptive learning algorithm that makes it possible to identify the analyzed events, and, from the practical point of view, this is an algorithm that gives an opportunity to estimate simultaneously the degree of “typicality”, to calculate the coordinates, to provide computer visualization of these events. The role of events is played by elements of a sequence of output signals of an arbitrary discrete stochastic dynamic system. In addition, the estimation of the “typicality” of events can be considered as the quantitative analysis of the studied system, while the visualization can be considered as its qualitative analysis.
Starting Page	540
Ending Page	553
Page Count	14
File Format	PDF
ISSN	10642307
Journal	Journal of Computer and Systems Sciences International
Volume Number	48
Issue Number	4
e-ISSN	15556530
Language	English
Publisher	SP MAIK Nauka/Interperiodica
Publisher Date	2009-08-21
Publisher Place	Dordrecht
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Control Robotics Mechatronics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Theoretical Computer Science Computer Networks and Communications Control and Systems Engineering Information Systems Computer Vision and Pattern Recognition Software

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