 Class-oriented techniques for reconstruction of dynamics from time seriesB.P. Bezruchko, V.I. Ponomarenko, D.A. Smirnov, I.V. Sysoev and M.D. Prokhorov Chaos, Solitons & Fractals, 2021, vol. 148, issue C Abstract: Reconstruction of dynamical systems from time series is an important problem intensively studied within nonlinear dynamics and time series analysis for the last three decades. Its solution is a tool to accomplish prediction, classification, diagnostics and many other tasks. Universal approaches are quite attractive, but more specific techniques based on prior information about a system under study often appear advantageous in practice. We present an overview of the works of our team where such “class-oriented” techniques have been developed for realistic situations differing by the degree of prior knowledge: fully known structure of the dynamics equations with an accent to dealing with hidden variables and partly known structure for time-delay systems and coupled phase oscillators. Keywords: Reconstruction of dynamical systems; Time series analysis; Parameter estimation; Hidden variables; Time-delay systems; Phase oscillators; Directional couplings (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:148:y:2021:i:c:s096007792100326x DOI: 10.1016/j.chaos.2021.110972 Access Statistics for this article Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros More articles in Chaos, Solitons & Fractals from Elsevier |
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