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Measurement Errors and Uncertainties : Theory and Practice
Measurement Errors and Uncertainties addresses the most important problems that physicists and engineers encounter when estimating errors and uncertainty. Building from the fundamentals of measurement theory, the author develops the theory of accuracy of measurements and offers a wealth of practical recommendations and examples of applications.
Introduzione alla teoria della misura e all’analisi funzionale = Introduction to measurement theory and functional analysis
Presents a treatment of the theory of measure from an abstract point of view, with particular emphasis on some aspects of interest in probability. The typical arguments of the theory of integration are developed in a rather in-depth way, trying where possible to deduce classical results from the modern setting of the theory as well. The text has a modular structure, with interconnections between the parts: some chapters deal with theoretical aspects, others are dedicated to more applied topics. Alongside the numerous examples, a wide range of exercises is proposed.
Explorations in Mathematical Physics : The Concepts Behind an Elegant Language
This book takes you on a tour of the main ideas forming the language of modern mathematical physics. Here you will meet novel approaches to concepts such as determinants and geometry, wave function evolution, statistics, signal processing, and three-dimensional rotations. You'll see how the accelerated frames of special relativity tell us about gravity. On the journey, you'll discover how tensor notation relates to vector calculus, how differential geometry is built on intuitive concepts, and how variational calculus leads to field theory. You will meet quantum measurement theory, along with Green functions and the art of complex integration, and finally general relativity and cosmology.
Elementi di Probabilità e Statistica
The authors' approach to Probability and Statistics is not based on measurement theory, but introduces the concept of probability and random number without using probability spaces. Trying to reduce formalism, the authors elaborate an introduction to probability more usable for students of computer science, engineering, statistics.
