Probing the correlations in composite signals

TL;DR

This paper explores how the Kolmogorov stochasticity parameter can quantify the randomness in composite signals, aiding in distinguishing signals with different regular and random properties, especially in astrophysical contexts.

Contribution

It introduces a method using the Kolmogorov stochasticity parameter to analyze correlations in composite signals, providing qualitative and quantitative criteria for signal behavior.

Findings

The Kolmogorov stochasticity parameter effectively distinguishes signals with varying degrees of randomness.

Numerical experiments demonstrate the method's applicability to astrophysical signals.

Criteria for signal behavior based on input parameters are established.

Abstract

The technique of degree of randomness is used to model the correlations in sequences containing various subsignals and noise. Kolmogorov stochasticity parameter enables to quantify the randomness in number sequences and hence appears as an efficient tool to distinguish the signals. Numerical experiments for a broad class of composite signals of regular and random properties enable to obtain the qualitative and quantitative criteria for the behavior of the descriptor depending on the input parameters typical to astrophysical signals.