A Novel Wave Decomposition for Oscillatory Signals

Oscillatory systems arise in the different science fields. Complex mathematical formulations with differential equations have been proposed to model the dynamics of these systems. While they have the advantage of having a direct physiological meaning, they are not useful in practice as a result of the parameter adjustment complexity and the presence of noise. In this paper, a novel decomposition approach in AM-FM components, competing with Fourier and other decompositions is presented. Several interesting theoretical properties are derived including the ordinary differential equations describing the signal. Furthermore, the usefulness in real practice is demonstrated to analyse signals associated to neuron synapses and by addressing other questions in neuroscience.

Automated summary

This paper introduces a novel signal decomposition method to address the complexity of parameter adjustment and noise limitations in simulating oscillatory systems. The method demonstrates practical utility in analyzing signals in neuroscience.