Selection of state variables and algorithms of parametric identification of the object by its kinematic characteristics
DOI:
https://doi.org/10.15587/2313-8416.2017.99049Keywords:
pattern recognition, fuzzy clustering, algorithms of parametric classification, generalized coordinates, Lame functionsAbstract
It is shown that algorithms of fuzzy clustering or algorithms of parametric classification can be used to solve the problem of qualitative identification under fuzzy data. It is suggested that in the conditions of masking the object as information signs for solving the recognition problem it is necessary to use the kinematic characteristics of their motion: the components of the velocity vectors and the acceleration of the characteristic points of the object in a system of generalized coordinates using Lame functions
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