Bispectral analysis, a technique based on high-order statistics, is extended to encompass time dependence for the case of coupled nonlinear oscillators. It is applicable to univariate as well as to multivariate data obtained, respectively, from one or more of the oscillators. It is demonstrated for a generic model of interacting systems whose basic units are the Poincaré oscillators. Their frequency and phase relationships are explored for different coupling strengths, both with and without Gaussian noise. The distinctions between additive linear or quadratic, and parametric (frequency modulated), interactions in the presence of noise are illustrated.
An extension of bispectral analysis to encompass time dependence for the case of coupled nonlinear oscillators. Stimulated applications of the bispectral technique to characterise heart-rate variability, renal and kidney blood flow, EEG waves, and ozone records. RAE_import_type : Journal article RAE_uoa_type : Physics