Signal prediction by anticipatory relaxation dynamics

TL;DR

The paper introduces anticipatory relaxation dynamics (ARD), a model-free, frequency-dependent method for real-time signal prediction that can forecast peaks and is characterized by its frequency response.

Contribution

It presents ARD as a novel, analytically characterized predictor that anticipates future signal values and peaks without relying on a specific model.

Findings

ARD predicts signals on average with high accuracy.

ARD can anticipate the occurrence of signal peaks.

ARD is characterized by a frequency response function.

Abstract

Real-time prediction of signals is a task often encountered in control problems as well as by living systems. Here a model-free prediction approach based on the coupling of a linear relaxation-delay system to a smooth, stationary signal is described. The resulting anticipatory relaxation dynamics (ARD) is a frequency-dependent predictor of future signal values. ARD not only approximately predicts signals on average but can anticipate the occurrence of signal peaks, too. This can be explained by recognizing ARD as an input/output system with negative group delay. It is completely characterized, including its prediction horizon, by its analytically given frequency response function.