Jump to ratings and reviews
Rate this book

Inverse Problem Theory and Methods for Model Parameter Estimation

Rate this book
The use of actual observations to infer the properties of a model is an inverse problem, which are often difficult as they may not have a unique solution. This book proposes a general approach that is valid for linear as well as for nonlinear problems. The philosophy is essentially probabilistic and allows the reader to understand the basic difficulties appearing in the resolution of inverse problems. The book attempts to explain how a method of acquisition of information can be applied to actual real-world problems, including many heuristic arguments. Prompted by recent developments in inverse theory, this text is a completely rewritten version of a 1987 book by the same author, and includes many algorithmic details for Monte Carlo methods, least-squares discrete problems, and least-squares problems involving functions. In addition, some notions are clarified, the role of optimization techniques is underplayed, and Monte Carlo methods are taken much more seriously.

352 pages, Paperback

First published December 20, 2004

9 people want to read

About the author

Ratings & Reviews

What do you think?
Rate this book

Friends & Following

Create a free account to discover what your friends think of this book!

Community Reviews

5 stars
7 (53%)
4 stars
6 (46%)
3 stars
0 (0%)
2 stars
0 (0%)
1 star
0 (0%)
Displaying 1 of 1 review
Profile Image for Ladan.
185 reviews481 followers
September 10, 2017
This book is a total masterpiece.I couldn't do my thesis without this comprehensive book.what a pity you are dead... RIP Tarantola :(
Displaying 1 of 1 review

Can't find what you're looking for?

Get help and learn more about the design.