DocumentCode :
1755590
Title :
Spectral Analysis for Nonstationary and Nonlinear Systems: A Discrete-Time-Model-Based Approach
Author :
Fei He ; Billings, S.A. ; Hua-Liang Wei ; Sarrigiannis, Ptolemaios G. ; Yifan Zhao
Author_Institution :
Dept. of Autom. Control & Syst. Eng., Univ. of Sheffield, Sheffield, UK
Volume :
60
Issue :
8
fYear :
2013
fDate :
Aug. 2013
Firstpage :
2233
Lastpage :
2241
Abstract :
A new frequency-domain analysis framework for nonlinear time-varying systems is introduced based on parametric time-varying nonlinear autoregressive with exogenous input models. It is shown how the time-varying effects can be mapped to the generalized frequency response functions (FRFs) to track nonlinear features in frequency, such as intermodulation and energy transfer effects. A new mapping to the nonlinear output FRF is also introduced. A simulated example and the application to intracranial electroencephalogram data are used to illustrate the theoretical results.
Keywords :
autoregressive processes; electroencephalography; frequency response; frequency-domain analysis; intermodulation; medical signal processing; spectral analysis; time-varying systems; discrete-time-model-based approach; energy transfer effects; frequency response functions; frequency-domain analysis; intermodulation; intracranial electroencephalogram; nonlinear time-varying systems; nonstationary system; parametric time-varying nonlinear autoregressive; spectral analysis; Analytical models; Brain modeling; Computational modeling; Frequency response; Time varying systems; Time-frequency analysis; Frequency response functions (FRFs); nonlinear and nonstationary systems; spectral analysis; system identification; time-varying systems; Algorithms; Brain; Computer Simulation; Data Interpretation, Statistical; Electroencephalography; Models, Neurological; Models, Statistical; Nonlinear Dynamics; Signal Processing, Computer-Assisted; Stochastic Processes;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2013.2252347
Filename :
6478782
Link To Document :
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