Physics Letters A, 381(6), 604–615p. (2017) DOI:10.1016/j.physleta.2016.12.028

Robust reconstruction of a signal from its unthresholded recurrence plot subject to disturbances

A. Sipers, P. Borm, R. Peeters

To make valid inferences from recurrence plots for time-delay embedded signals, two underlying key questions are: (1) to what extent does an unthresholded recurrence (URP) plot carry the same information as the signal that generated it, and (2) how does the information change when the URP gets distorted. We studied the first question in our earlier work [1], where it was shown that the URP admits the reconstruction of the underlying signal (up to its mean and a choice of sign) if and only if an associated graph is connected. Here we refine this result and we give an explicit condition in terms of the embedding parameters and the discrete Fourier spectrum of the URP. We also develop a method for the reconstruction of the underlying signal which overcomes several drawbacks that earlier approaches had. To address the second question we investigate robustness of the proposed reconstruction method under disturbances. We carry out two simulation experiments which are characterized by a broad band and a narrow band spectrum respectively. For each experiment we choose a noise level and two different pairs of embedding parameters. The conventional binary recurrence plot (RP) is obtained from the URP by thresholding and zero-one conversion, which can be viewed as severe distortion acting on the URP. Typically the reconstruction of the underlying signal from an RP is expected to be rather inaccurate. However, by introducing the concept of a multi-level recurrence plot (MRP) we propose to bridge the information gap between the URP and the RP, while still achieving a high data compression rate. We demonstrate the working of the proposed reconstruction procedure on MRPs, indicating that MRPs with just a few discretization levels can usually capture signal properties and morphologies more accurately than conventional RPs.


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