M. G. Zhartybayeva, M. M. Tatur, M. M. Shaverdo, K. T. Iskakov, “Methods of reducing the computational complexity of fuzzy inference algorithms for implementation on a microcontroller with limited computational resources”, Eurasian Journal of Mathematical and Computer Applications, 2019, Volume 7, Issue 1,Pages <nobr>65

This article is cited in 1 paper

Methods of reducing the computational complexity of fuzzy inference algorithms for implementation on a microcontroller with limited computational resources

M. G. Zhartybayeva^a, M. M. Tatur^b, M. M. Shaverdo^b, K. T. Iskakov^a

^a L.Gumilyov Eurasian National University, Pushkin st. 11, Faculty of information Technologies, Astana, Kazakhstan
^b Belarusian State University of Informatics and Radioelectronics, Minsk, Belarus, Department of Electronic Computing Machines

Abstract: In our work we suggest the most effective ways to reduce the complexity of computing fuzzy inference algorithms, which do not lead to a valuable decrease in the control quality. Our suggestions will be analytically formulated, illustrated with examples and results of model experiments.

Keywords: fuzzy inference algorithms, fuzzy logic, control system.

MSC: 03B52, 94D05

Language: English

DOI: 10.32523/2306-6172-2019-7-1-65-78