Decomposing spectral and phasic differences in non-linear features between datasets


When employing non-linear methods to characterise complex systems, it is important to determine to what extent they are capturing genuine non-linear phenomena that could not be assessed by simpler spectral methods. Specifically, we are concerned with the problem of quantifying spectral and phasic effects on an observed difference in a non-linear feature between two systems (or two states of the same system). Here we derive, from a sequence of null models, a decomposition of the difference in an observable into spectral, phasic, and spectrum-phase interaction components. Our approach makes no assumptions about the structure of the data and adds nuance to a wide range of time series analyses.

Physical Review Letters, 127
Pedro Mediano
Pedro Mediano
Coffee-powered beast-machine

Computational neuroscientist interested in synergy, information theory, and complexity.