• Menu
  • Skip to right header navigation
  • Skip to main content
  • Skip to secondary navigation
  • Skip to primary sidebar

OnlineProgrammingBooks.com

Legally Free Computer Books

  • All Categories
  • All Books
  • All Categories
  • All Books
  • About Us
  • Privacy policy
  • Disclaimer
  • Subscribe
  • Contact
You are here: Home ▶ Mathematics ▶ Inverse Problem Theory and Model Parameter Estimation

Inverse Problem Theory and Model Parameter Estimation

March 24, 2006

Inverse Problem Theory and Model Parameter Estimation

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.

Book Description

The first part of this book deals exclusively with discrete inverse problems with a finite number of parameters. Some real problems are naturally discrete, while others contain functions of a continuous variable and can be discretized if the functions under consideration are smooth enough compared to the sampling length, or if the functions can conveniently be described by their development on a truncated basis. The advantage of a discretized point of view for problems involving functions is that the mathematics is easier. The disadvantage is that some simplifications arising in a general approach can be hidden when using a discrete formulation. (Discretizing the forward problem and setting a discrete inverse problem is not always equivalent to setting a general inverse problem and discretizing for the practical computations.)
The second part of the book deals with general inverse problems, which may contain such functions as data or unknowns. As this general approach contains the discrete case in particular, the separation into two parts corresponds only to a didactical purpose.
Although this book contains a lot of mathematics, it is not a mathematical book. It tries to explain how a method of acquisition of information can be applied to the actual world, and many of the arguments are heuristic.

Table of Contents

  • The General Discrete Inverse Problem
  • Monte Carlo Methods
  • The Least-Squares Criterion
  • Least-Absolute-Values Criterion and Minimax Criterion
  • Functional Inverse Problems

Download Free PDF / Read Online

Author(s): Albert Tarantola
Format(s): PDF
File size: 20.08 MB
Number of pages: 358
Link: Download.

Similar Books:

  1. A Computational Introduction to Number Theory and Algebra
  2. Industrial Robotics: Theory, Modelling and Control
  3. Scene Reconstruction Pose Estimation and Tracking
  4. Elementary Number Theory
  5. Graph Theory with Applications
Previous Post: « Algorithms: Fundamental Techniques
Next Post: Basic Computing Using Windows »

Primary Sidebar

Get Latest Updates

  • Facebook
  • Pinterest
  • RSS
  • Twitter
  • YouTube
  • About Us
  • Privacy policy
  • Disclaimer
  • Subscribe
  • Contact

Copyright © 2006–2025 OnlineProgrammingBooks.com