Geodesic
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, Tome 7 (2019) no. 1, pp. 65-78

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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. 
@article{EJMCA_2019_7_1_a4,
     author = {M. G. Zhartybayeva and M. M. Tatur and M. M. Shaverdo and K. T. Iskakov},
     title = {Methods of reducing the computational complexity of fuzzy inference algorithms for implementation on a microcontroller with limited computational resources},
     journal = {Eurasian journal of mathematical and computer applications},
     pages = {65--78},
     publisher = {mathdoc},
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     number = {1},
     year = {2019},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/EJMCA_2019_7_1_a4/}
}
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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, Tome 7 (2019) no. 1, pp. 65-78. http://geodesic.mathdoc.fr/item/EJMCA_2019_7_1_a4/