Large-scale Inverse Problems and Quantification of Uncertainty

by Editor: Lorenz Biegler (Carnegie Mellon, USA ); Co-Editor: George Biros (University of Pennsylvania, USA ); Co-Editor: Omar Ghattas (Univesity of Texas at Austin, USA ); Co-Editor: Matthias Heinkenschloss (Rice University, USA ); Co-Editor: Davi

• ISBN13: 9780470685860
• ISBN10: 0470685867
• Format: eBook
• Copyright: 2010-09-01
• Publisher: Wiley

Summary

Large scale inverse problems and associated uncertainty quantification has become an important area of research, central to a wide range of science and engineering applications. Written by leading experts in the field, Large-scale Inverse Problems and Quantification of Uncertainty focuses on the computational methods used to analyze and simulate inverse problems. The text provides PhD students, researchers, advanced undergraduate students, and engineering practitioners with the perspectives of researchers in areas of inverse problems and data assimilation, ranging from statistics and large-scale optimization to applied and computational mathematics and high performance computing.