Detecting Unstable Periodic Orbits in Chaotic Experimental Data

A new method is proposed for detecting unstable periodic orbits and their linear stability properties from chaotic experimental time series. Illustrative examples are presented for both numerically and experimentally generated time series. The statistical significance of the results is assessed using surrogate data.