Abstract
An elementary introduction to the theory of artificial neural networks is given. Principles of their structural composition are presented. Methods for the neural-network training commonly used for different levels of intellectual control of mechatronic systems are formulated and substantiated. Neural-network approaches to typical problems of classification, digital signal processing, data compression, function interpolation and extrapolation, associative behavior, and optimization are stated.
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Translated from Fundamentalnaya i Prikladnaya Matematika, Vol. 11, No. 8, pp. 81–103, 2005.
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Golubev, Y.F. Neural networks in mechatronics. J Math Sci 147, 6607–6622 (2007). https://doi.org/10.1007/s10958-007-0497-3
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DOI: https://doi.org/10.1007/s10958-007-0497-3