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Efficient data assimilation for spatiotemporal chaos: A local ensemble transform Kalman filter

- B. Hunt, E. Kostelich, I. Szunyogh
- Computer Science, Physics
- 28 November 2005

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A Local Ensemble Kalman Filter for Atmospheric Data Assimilation

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Prevalence: a translation-invariant “almost every” on infinite-dimensional spaces

- B. Hunt
- Mathematics
- 1 October 1992

We present a measure-theoretic condition for a property to hold «almost everywhere» on an infinite-dimensional vector space, with particularemphasis on function spaces such as C k and L p . Like the… Expand

Model-Free Prediction of Large Spatiotemporally Chaotic Systems from Data: A Reservoir Computing Approach.

- Jaideep Pathak, B. Hunt, M. Girvan, Zhixin Lu, E. Ott
- Computer Science, Medicine
- Physical review letters
- 12 January 2018

We demonstrate the effectiveness of using machine learning for model-free prediction of spatiotemporally chaotic systems of arbitrarily large spatial extent and attractor dimension purely from… Expand

Reservoir observers: Model-free inference of unmeasured variables in chaotic systems.

- Zhixin Lu, Jaideep Pathak, B. Hunt, M. Girvan, R. Brockett, E. Ott
- Mathematics, Medicine
- Chaos
- 5 April 2017

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Local low dimensionality of atmospheric dynamics.

- D. Patil, B. Hunt, E. Kalnay, J. Yorke, E. Ott
- Environmental Science, Medicine
- Physical review letters
- 25 June 2001

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Four-dimensional ensemble Kalman filtering

Ensemble Kalman filtering was developed as a way to assimilate observed data to track the current state in a computational model. In this paper we show that the ensemble approach makes possible an… Expand

Optimal orbits of hyperbolic systems

- Guo-Cheng Yuan, B. Hunt
- Mathematics
- 1 July 1999

Given a dynamical system and a function f from the state space to the real numbers, an optimal orbit for f is an orbit over which the time average of f is maximal. In this paper we consider some… Expand

Balance and Ensemble Kalman Filter Localization Techniques

- S. Greybush, E. Kalnay, T. Miyoshi, K. Ide, B. Hunt
- Mathematics
- 1 February 2011

Abstract In ensemble Kalman filter (EnKF) data assimilation, localization modifies the error covariance matrices to suppress the influence of distant observations, removing spurious long-distance… Expand

A Guide to MATLAB®: For Beginners and Experienced Users

- B. Hunt, R. Lipsman, J. Rosenberg
- Computer Science
- 20 October 2014

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