Parameter Estimation for PDEs using Stochastic Methods

ISBN-13: 9783659927324 / Angielski / Miękka / 2019 / 152 str.

Roxana Elena Tanase

Opis

The aim of this book is to compare the efficiency of different algorithms on estimating parameters that arise in partial differential equations: Kalman Filters (Ensemble Kalman Filter, Stochastic Collocation Kalman Filter, Karhunen-Lo`eve Ensemble Kalman Filter, Karhunen- Lo`eve Stochastic Collocation Kalman Filter), Markov-Chain Monte Carlo sampling schemes and Adjoint variable-based method. We also present the theoretical results for stochastic optimal control for problems constrained by partial differential equations with random input data in a mixed finite element form. We verify experimentally with numerical simulations using Adjoint variable-based method with various identification objectives that either minimize the expectation of a tracking cost functional or minimize the difference of desired statistical quantities in the appropriate Lp norm.

O autorze

Tanase, Roxana Elena
Dr. Roxana Elena Tanase : B.S. in Mathematics and Computer Science, University ofBucharest, 2005.M.S. in Mathematics, University of Bucharest, 2007.M.S. in Mathematics, University of Cincinnati, 2009.