Literature DB >> 11017653

Prediction of spatiotemporal time series based on reconstructed local states

.   

Abstract

Spatiotemporal time series are analyzed and predicted using reconstructed local states. As numerical examples the evolution of a Kuramoto-Sivashinsky equation and a coupled map lattice are predicted from previously sampled data.

Year:  2000        PMID： 11017653     DOI： 10.1103/PhysRevLett.84.1890

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN： 0031-9007            Impact factor:   9.161


  4 in total

1.  Estimating varying coefficients for partial differential equation models.

Authors:  Xinyu Zhang; Jiguo Cao; Raymond J Carroll
Journal:  Biometrics       Date:  2017-01-11       Impact factor: 2.571

2.  Evidence-based modeling of network discharge dynamics during periodic pacing to control epileptiform activity.

Authors:  Keith Bush; Gabriella Panuccio; Massimo Avoli; Joelle Pineau
Journal:  J Neurosci Methods       Date:  2011-12-08       Impact factor: 2.390

3.  Parameter Estimation of Partial Differential Equation Models.

Authors:  Xiaolei Xun; Jiguo Cao; Bani Mallick; Raymond J Carroll; Arnab Maity
Journal:  J Am Stat Assoc       Date:  2013       Impact factor: 5.033

4.  Optimal solid state neurons.

Authors:  Kamal Abu-Hassan; Joseph D Taylor; Paul G Morris; Elisa Donati; Zuner A Bortolotto; Giacomo Indiveri; Julian F R Paton; Alain Nogaret
Journal:  Nat Commun       Date:  2019-12-03       Impact factor: 14.919
  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.