Optimal Estimation of Dynamically Evolving Diffusivities
Abstract
The augmented, iterated Kalman smoother is applied to system identification for inverse problems in evolutionary differential equations. In the augmented smoother, the unknown, time dependent coefficients are included in the state vector and have a stochastic component. At each step in the iteration, the estimate of the time evolution of the coefficients is linear. We update the slowly varying mean temperature and conductivity by averaging the estimates of the Kalman smoother. Applications include the estimation of anomalous diffusion coefficients in turbulent fluids and the plasma rotation velocity in plasma tomography.
 Publication:

Journal of Computational Physics
 Pub Date:
 November 1994
 DOI:
 10.1006/jcph.1994.1173
 arXiv:
 arXiv:1803.03911
 Bibcode:
 1994JCoPh.115....1R
 Keywords:

 Statistics  Methodology;
 Electrical Engineering and Systems Science  Signal Processing;
 Mathematics  Optimization and Control;
 Physics  Data Analysis;
 Statistics and Probability
 EPrint:
 J. Computational Physics Vol 115, pg 111, 1995