Time Series meet Network Science

Abstract

In the last years, ideas and methods from network science have been applied to study the structure of time series and signals, thereby building a bridge between nonlinear dynamics, time series analysis and graph theory. In this talk I will focus on a particular approach, namely the family of visibility algorithms, and will give an overview of the main results that we have obtained recently. In particular, I will depict several case studies where concrete problems in nonlinear dynamics, stochastic processes and statistical physics can be easily mapped, via visibility algorithms, to the study of the topological properties of classes of visibility graphs. I will conclude with a summary of open problems and applications.