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Anglický jazyk
Parameter Estimation for PDEs using Stochastic Methods
Autor: Roxana Elena Tanase
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... Viac o knihe
Na objednávku
57.33 €
bežná cena: 63.70 €
O knihe
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.
- Vydavateľstvo: LAP LAMBERT Academic Publishing
- Rok vydania: 2019
- Formát: Paperback
- Rozmer: 220 x 150 mm
- Jazyk: Anglický jazyk
- ISBN: 9783659927324
