**Inverse Problem Theory and Methods for Model Parameter Estimation**

by Albert Tarantola

**Publisher**: SIAM 2004**ISBN/ASIN**: 0898715725**ISBN-13**: 9780898715729**Number of pages**: 358

**Description**:

The first part of the book deals exclusively with discrete inverse problems with a finite number of parameters, while the second part of the book deals with general inverse problems. The book is directed to all scientists, including applied mathematicians, facing the problem of quantitative interpretation of experimental data in fields such as physics, chemistry, biology, image processing, and information sciences. Considerable effort has been made so that this book can serve either as a reference manual for researchers or as a textbook in a course for undergraduate or graduate students.

Download or read it online for free here:

**Download link**

(20MB, PDF)

## Similar books

**An Introduction to Stochastic PDEs**

by

**Martin Hairer**-

**arXiv**

This text is an attempt to give a reasonably self-contained presentation of the basic theory of stochastic partial differential equations, taking for granted basic measure theory, functional analysis and probability theory, but nothing else.

(

**9081**views)

**Design of Comparative Experiments**

by

**R. A. Bailey**-

**Cambridge University Press**

This book develops a coherent framework for thinking about factors that affect experiments and their relationships, including the use of Hasse diagrams. The book is ideal for advanced undergraduate and beginning graduate courses.

(

**16684**views)

**Introduction to Probability, Statistics, and Random Processes**

by

**Hossein Pishro-Nik**-

**Kappa Research, LLC**

This book introduces students to probability, statistics, and stochastic processes. It can be used by both students and practitioners in engineering, sciences, finance, and other fields. It provides a clear and intuitive approach to these topics.

(

**5875**views)

**Correlation and Causality**

by

**David A. Kenny**-

**John Wiley & Sons Inc**

This text is a general introduction to the topic of structural analysis. It presumes no previous acquaintance with causal analysis. It is general because it covers all the standard, as well as a few nonstandard, statistical procedures.

(

**11168**views)