Data Driven Modeling
&
Scientific Computation

Data-Driven Modeling & Scientific Computation

Lecture 1

 

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Data Assimilation 1: This lecture provides an introduction to data assimilation methods and the Kalman filter.

 

Lecture 2

 

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Data Assimilation 2: This lecture generalizes data assimilation to dynamical systems and introduces the Ensemble Kalman Filter (EKF).

 

Lecture 3

 

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Data Assimilation 3: This lecture implements a basic Kalman filtering and data assimilation scheme on the Lorenz equations.

 

 

 

KEY REFERENCES

J. N. Kutz, NOTES — CHAPTER 21 (Kutz, Data-Driven Modeling & Scientific Computation, Oxford 2013)

Miller, Ghil & Gauthiez, Data Assimilation in Strongly Nonlinear Dynamical Systems J. Atmos. Sci. 51 (1994) 1037

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