A new method to embed time-series data and for parameter identification

Abstract

This paper develops a scheme to estimate the derivatives of a discretely sampled data more accurately than traditional methods. The method is based on applying singular-value decomposition to Taylor's expansion but in a matrix form. The validity and robustness to noise of the proposed scheme are illustrated by numerical experiments.