The EKF-AUS-NL algorithm implemented without the linear tangent model and in presence of parametric model error-Reference-Cited by-同舟云学术

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The EKF-AUS-NL algorithm implemented without the linear tangent model and in presence of parametric model error

Published:2018-01 Issue: Volume:7 Page:28-33
ISSN:2352-7110
Container-title:SoftwareX
language:en
Short-container-title:SoftwareX

Author:

Palatella Luigi^ORCID,Grasso Fabio

Publisher

Elsevier BV

Subject

Computer Science Applications,Software

Reference18 articles.

1. Chaos and weather forecasting: the role of the unstable subspace in predictability and state estimation problems;Trevisan;Int J Bifurcation Chaos,2011

2. Lyapunov vectors and assimilation in the unstable subspace: theory and applications;Palatella;J Phys A,2013

3. Interaction of Lyapunov vectors in the formulation of the nonlinear extension of the Kalman filter;Palatella;Phys Rev E,2015

4. Lorenz EN. Predictability: A problem partly solved. In: Proc. seminar on predictability, vol. 1. 1996.

5. A solution to the simultaneous localization and map building (SLAM) problem;Dissanayake;IEEE Transa Robot Autom,2001

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Data Assimilation for Chaotic Dynamics;Data Assimilation for Atmospheric, Oceanic and Hydrologic Applications (Vol. IV);2021-11-10

2. Chaotic dynamics and the role of covariance inflation for reduced rank Kalman filters with model error;Nonlinear Processes in Geophysics;2018-09-04

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