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Technology for data acquisition in diagnosis processes by means of the identification using Volterra models

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3 Author(s)
Pavlenko Vitaliy ; Department of Computer control systems, Odessa national polytechnical university 65044, Shevchenko av. 1, Odessa, Ukraine ; Fomin Oleksandr ; Ilyin Vladimir

The method of a black-box diagnostics, founded on nonparametric identification of objects using integro-power Volterra series is offered. It provides a set of diagnostic features formed on base of multidimensional Volterra kernels: discrete values of Volterra kernels, heuristic features, moments and wavelet transform coefficients. It is researched a self-descriptiveness of provided features using classifier on base of neural nets. The diagnostic spaces are formed by method of all features combination selection.

Published in:

Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, 2009. IDAACS 2009. IEEE International Workshop on

Date of Conference:

21-23 Sept. 2009