EconPapers    
Economics at your fingertips  
 

Redefining embedding robustness: A Wasserstein-based analysis of delay–dimension dynamics

Tsuyoshi Miyata, Atsushi Ichikawa and Takayuki Sato

Chaos, Solitons & Fractals, 2026, vol. 210, issue P1

Abstract: Delay-coordinate embedding provides a fundamental framework for reconstructing state-space structures of dynamical systems from scalar time series. While Takens' embedding theorem guarantees the existence and robustness of valid embeddings, it does not prescribe unique optimal values for the time delay τ or embedding dimension m. In practice, these parameters are typically selected using heuristic criteria such as average mutual information (AMI) and false nearest neighbors (FNN), which often depend on implementation details and data length.

Keywords: Delay-coordinate embedding; State-space reconstruction; Wasserstein distance; Distribution-level analysis; Chaotic dynamical systems; Robustness (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077926007599
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:210:y:2026:i:p1:s0960077926007599

DOI: 10.1016/j.chaos.2026.118618

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
Bibliographic data for series maintained by Thayer, Thomas R. ().

 
Page updated 2026-07-15
Handle: RePEc:eee:chsofr:v:210:y:2026:i:p1:s0960077926007599