Estimating initial conditions in coupled map lattices from noisy time series using symbolic vector dynamics

Kai Wang*, Wenjiang Pei, Zhenya He, Yiu Ming CHEUNG

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

In this Letter, we investigate the symbolic vector dynamics method for initial condition estimation in additive white Gaussian noisy environment. We apply this scheme not only to the skewed-tent-CMLs and logistic-CMLs but also to the piecewise-linear-CMLs and Chebyshev-CMLs. We also discuss the symbol vector error probability in additive white Gaussian noisy condition, and evaluate the performance of this scheme at high signal-to-noise ratio (SNR). It is found that the SNR, the total number of CMLs' site and the length of generating partition will affect the symbol vector error probability. Both theoretical and experimental results show that this algorithm enables us to recover initial condition of CMLs exactly in both noisy and noise free cases. Therefore, we provide novel analytical techniques for understanding turbulences in coupled map lattices.

Original languageEnglish
Pages (from-to)316-321
Number of pages6
JournalPhysics Letters, Section A: General, Atomic and Solid State Physics
Volume367
Issue number4-5
DOIs
Publication statusPublished - 30 Jul 2007

Scopus Subject Areas

  • Physics and Astronomy(all)

User-Defined Keywords

  • Coupled mode analysis
  • Initial condition estimation
  • Signal processing
  • Symbols vector dynamics

Fingerprint

Dive into the research topics of 'Estimating initial conditions in coupled map lattices from noisy time series using symbolic vector dynamics'. Together they form a unique fingerprint.

Cite this