title: Spectral analysis for nonstationary and nonlinear systems: a discrete-time-model-based approach.
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.
authors.affiliation: Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield, S1 3JD, UK. f.he@sheffield.ac.uk
authors.forename: Fei
authors.initials: F
authors.lastname: He
authors.forename: Stephen A
authors.initials: SA
authors.lastname: Billings
authors.forename: Hua-Liang
authors.initials: HL
authors.lastname: Wei
authors.forename: Ptolemaios G
authors.initials: PG
authors.lastname: Sarrigiannis
authors.forename: Yifan
authors.initials: Y
authors.lastname: Zhao
mesh_terms: D000465:Algorithms; D001921:Brain / Q000502:physiology*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods*; D008959:Models, Neurological; D015233:Models, Statistical; D017711:Nonlinear Dynamics; D012815:Signal Processing, Computer-Assisted; D013269:Stochastic Processes