Data Fitting and Uncertainty: A practical introduction to by Tilo Strutz

By Tilo Strutz

The topic of knowledge becoming bridges many disciplines, specially these usually facing data like physics, arithmetic, engineering, biology, economic system, or psychology, but additionally newer fields like computing device imaginative and prescient. This booklet addresses itself to engineers and computing device scientists or corresponding undergraduates who're drawn to facts becoming via the tactic of least-squares approximation, yet haven't any or basically restricted pre-knowledge during this box. skilled readers will locate in it new rules or may take pleasure in the ebook as an invaluable paintings of reference. Familiarity with easy linear algebra is useful notwithstanding no longer crucial because the publication encompasses a self-contained advent and provides the tactic in a logical and obtainable model. the first objective of the textual content is to give an explanation for how info becoming through least squares works. The reader will locate that the emphasis of the publication is on functional concerns, now not on theoretical difficulties. additionally, the booklet allows the reader to layout personal software program implementations with application-specific version capabilities in keeping with the great dialogue of numerous examples. The textual content is followed with operating resource code in ANSI-C for becoming with weighted least squares together with outlier detection.

The content:
advent to Data-Fitting difficulties – Estimation of version Parameters by means of Least-Squares – Weights and Outliers – Uncertainty of effects – Matrix Algebra – the belief at the back of Least Squares – Supplemental instruments and Methods

aim Groups:
engineers, computing device scientists, physicists and software program programmers
undergraduates of engineering, machine technology, physics

concerning the author:
Dr.-Ing. habil. Tilo Strutz is professor at Hochschule für Telekommunikation Leipzig (University of technologies, Deutsche Telekom AG). His services is starting from common sign processing to photo processing to info compression.

Show description

Read or Download Data Fitting and Uncertainty: A practical introduction to weighted least squares and beyond PDF

Similar signal processing books

Survivability and Traffic Grooming in WDM Optical Networks

The arrival of fiber optic transmission structures and wavelength department multiplexing has ended in a dramatic raise within the usable bandwidth of unmarried fiber structures. This ebook offers unique insurance of survivability (dealing with the chance of wasting huge volumes of site visitors information because of a failure of a node or a unmarried fiber span) and site visitors grooming (managing the elevated complexity of smaller consumer requests over excessive potential facts pipes), either one of that are key concerns in sleek optical networks.

Principles of Semiconductor Network Testing (Test & Measurement)

This publication gathers jointly entire details which attempt and approach execs will locate important. The options defined may help make sure that try tools and knowledge gathered replicate real gadget functionality, instead of 'testing the tester' or being misplaced within the noise flooring. This e-book addresses the basic concerns underlying the semiconductor try self-discipline.

Opportunistic Spectrum Sharing and White Space Access: The Practical Reality

Information the paradigms of opportunistic spectrum sharing and white area entry as powerful capacity to fulfill expanding call for for high-speed instant verbal exchange and for novel instant conversation functions This ebook addresses opportunistic spectrum sharing and white area entry, being rather aware of sensible concerns and ideas.

From photon to pixel : the digital camera handbook

The camera conceals extraordinary technological techniques that have an effect on the formation of the picture, the colour illustration or computerized measurements and settings. ** From photon to pixel photon ** describes the gadget either from the perspective of the physics of the phenomena concerned, as technical parts and software program it makes use of.

Additional resources for Data Fitting and Uncertainty: A practical introduction to weighted least squares and beyond

Sample text

However, in a large number of cases, this reliability is not known in advance, which means the weights have to be estimated (see Chapter 3). When observations are weighted, the procedure is primarily called generalised least squares or weighted least squares in contrast to ordinary least squares with wi = w = const. The influence of a chosen set of parameters a on χ2 can be visualised using what are called error surfaces. The procedure for minimising χ2 has to find the global minimum in that surface.

12: Comparison of sigmoid and hyperbolic-tangent function Instead of presenting single pairs of xi and yi followed by weights adjustment using back-propagation of errors through the single layers as described in many textbooks, the training of the neural network can now be performed simply using a data-fitting procedure. Combined with a suitable weighting scheme (see Chapter 3), outliers in the training set can also be treated properly. 1 What is the difference between conditions and observations?

9 What are the drawbacks of nonlinear model functions? 10 Itemise different methods for the estimation of initial parameter values. 11 Explain the relation between least squares and neural networks. 12 How must the fitting procedure be altered if there is more than one observation per condition x? 13 Given the linear model function f (x|a) = a1 · x + a2 · x2 + a3 · ex + a4 · sin(x) , what is the Jacobian matrix? 14 How many parameters have to be estimated in a 2-3-2 neural network? 1 What are the weights good for?

Download PDF sample

Rated 4.58 of 5 – based on 47 votes