Open AccessNOISE IMMUNITY RESEARCH FOR NONLINEAR DYNAMICAL SYSTEMS IDENTIFICATION BASED ON VOLTERRA MODEL IN FREQUENCY DOMAIN
Author(s) -
Vitaliy Pavlenko,
Sergei Pavlenko,
Viktor Speranskyy
Publication year - 2014
Publication title -
computing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.184
H-Index - 11
eISSN - 2312-5381
pISSN - 1727-6209
DOI - 10.47839/ijc.13.1.619
Subject(s) - frequency domain , noise (video) , computer science , nonlinear system , volterra series , identification (biology) , system identification , matlab , interpolation (computer graphics) , nonlinear system identification , noise immunity , algorithm , control theory (sociology) , artificial intelligence , data mining , telecommunications , physics , measure (data warehouse) , motion (physics) , botany , control (management) , quantum mechanics , image (mathematics) , computer vision , biology , operating system , transmission (telecommunications)
The accuracy and noise immunity of the interpolation method of nonlinear dynamical systems identification based on the Volterra model in the frequency domain is studied in this paper. The polyharmonic signals are used for the testing the method. The algorithmic and software toolkit in Matlab is developed for the identification procedure. This toolkit is used to construct the informational models of test system and communication channel. The model is built as a first-, second- and third-order amplitude–frequency and phase–frequency characteristics. The comparison of obtained characteristics with previous works is given. Wavelet denoising is studied and applied to reduce measurement noise.