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Adaptive filters cascade applied to a frequency identification improvement problem
Author(s) -
Aranovskiy Stanislav V.,
Bobtsov Alexey A.,
Pyrkin Anton A.,
Gritcenko Polina A.
Publication year - 2016
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.2602
Subject(s) - cascade , control theory (sociology) , identification (biology) , filter (signal processing) , stability (learning theory) , adaptive filter , computer science , signal (programming language) , lyapunov function , mathematics , algorithm , engineering , artificial intelligence , nonlinear system , physics , computer vision , biology , programming language , botany , control (management) , chemical engineering , quantum mechanics , machine learning
Summary Problem of frequency identification performance improvement for a single‐tone sinusoidal signal is solved via construction of an adaptive filters cascade. The cascade consists of adaptive band‐pass filters tuned by estimates of the frequency provided by a given identification algorithm. Stability of the cascade is studied and boundedness of trajectories is proven with Lyapunov analysis under certain assumption on identification algorithm. Numerical simulations are given illustrating improved identification performance for different identification algorithms. Copyright © 2015 John Wiley & Sons, Ltd.