Delay reconstruction for multiprobe signals

Abstract

A physical system governed by low-dimensional dynamics may be described completely with just a few measurements. Once one has such a description, any further measurements are redundant-one ought to be able to determine the results from what one already knows. Here we apply this idea to multivariate time series; we use the signal in one of the channels to build a model of the underlying system, then use the model to predict all the other channels. We demonstrate the method on a signal from a fluid-mechanical experiment, then discuss the implications for signal compression and for the secrecy of messages masked by chaotic nois