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On one approach to the approximation of solutions to the direct kinematics problem of parallel manipulators

On one approach to the approximation of solutions to the direct kinematics problem of parallel... AbstractAny real continuous bounded function of many variables is representable as a superposition of functions of one variable and addition. Depending on the type of superposition, the requirements for the functions of one variable differ. The article investigated one of the options for the numerical implementation of such a superposition proposed by Sprecher. The superposition was presented as a three-layer Feedforward neural network, while the functions of the first’s layer were considered as a generator of space-filling curves (Peano curves). The resulting neural network was applied to the problems of direct kinematics of parallel manipulators. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Open Computer Science de Gruyter

On one approach to the approximation of solutions to the direct kinematics problem of parallel manipulators

Open Computer Science , Volume 10 (1): 6 – Jan 1, 2020

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Publisher
de Gruyter
Copyright
© 2020 Andrei Gorchakov et al., published by De Gruyter
eISSN
2299-1093
DOI
10.1515/comp-2020-0007
Publisher site
See Article on Publisher Site

Abstract

AbstractAny real continuous bounded function of many variables is representable as a superposition of functions of one variable and addition. Depending on the type of superposition, the requirements for the functions of one variable differ. The article investigated one of the options for the numerical implementation of such a superposition proposed by Sprecher. The superposition was presented as a three-layer Feedforward neural network, while the functions of the first’s layer were considered as a generator of space-filling curves (Peano curves). The resulting neural network was applied to the problems of direct kinematics of parallel manipulators.

Journal

Open Computer Sciencede Gruyter

Published: Jan 1, 2020

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