Detection of lag synchronization based on matrices of delayed differences

• Published in: Communications in nonlinear science & numerical simulation Vol. 116; p. 106864
• Main Authors: Smidtaite, Rasa, Saunoriene, Loreta, Ragulskis, Minvydas
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.01.2023
• Subjects: Delayed difference; Feature extraction; Lag synchronization; Optimal time lag; Feature extraction; Lag synchronization; Delayed difference; Optimal time lag
• ISSN: 1007-5704; 1878-7274
• DOI: 10.1016/j.cnsns.2022.106864

The algorithm for the detection of lag synchronization from time series data is presented in this paper. Multi-variate time series data are re-organized into a sequence of perfect matrices of delayed Lagrange differences and mapped into a two-dimensional pattern of discriminants. The minimization of this pattern yields a discrete sequence of time lags with a high resolution in time. The proposed technique is capable to detect lag synchronization between chaotic signals contaminated by noise. The proposed technique is also exploited as the feature extraction algorithm for the detection of cyclic alternating patterns in sleep. Computational experiments are used to demonstrate the efficacy of the proposed algorithm. •A novel approach for the detection of lag synchronization is presented in this paper.•Minimization of discriminants of delayed differences yields a sequence of time lags.•Algorithm detects lag synchronization between chaotic signals contaminated by noise.•Cyclic alternating patterns in sleep are detected by the feature extraction algorithm.