Description
Data Fitting and Uncertainty (2nd Ed., 2nd revised and extended ed. 2016)
A practical introduction to weighted least squares and beyond
Author: Strutz Tilo
Language: EnglishSubjects for Data Fitting and Uncertainty:
281 p. · 16.8x24 cm · Soft-cover
Description
/li>Contents
/li>Biography
/li>Comment
/li>
Among others the book covers following topics
* fitting of linear and nonlinear functions with one- or multi-dimensional variables
* weighted least-squares
* outlier detection
* evaluation of the fitting results
* different optimisation strategies
* combined fitting of different model functions
* total least-squares approach with multi-dimensional conditions
Framework of Least-Squares Method.- Introduction to Data-Fitting Problems.- Estimation of Model Parameters by the Method of Least Squares.- Weights and Outliers.- Uncertainty of Results.- Mathematics, Optimisation Methods, and Add ons.- Matrix Algebra.- The Idea behind Least Squares.- Supplemental Tools and Methods.- A Comparison of Approaches to Outlier Detection.- Implementation.
Dr.-Ing. habil. Tilo Strutz is professor at Leipzig University of Telecommunications (Deutsche Telekom). His expertise is ranging from general signal processing to special problems of image processing and data compression.
Fast guide to Data Fitting and Uncertainty
A self-contained introduction
Design your own software implementations