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This article is cited in 1 scientific paper (total in 1 paper)
Methods of reducing the computational complexity of fuzzy inference algorithms for implementation on a microcontroller with limited computational resources
M. G. Zhartybayevaa, M. M. Taturb, M. M. Shaverdob, K. T. Iskakova 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.
Citation:
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, 7:1 (2019), 65–78
Linking options:
https://www.mathnet.ru/eng/ejmca132 https://www.mathnet.ru/eng/ejmca/v7/i1/p65
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Abstract page: | 88 | Full-text PDF : | 41 |
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