Statistical Physics For Electrical Engineering
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Statistical Physics for Electrical Engineering
The main body of this book is devoted to statistical physics, whereas much less emphasis is given to thermodynamics. In particular, the idea is to present the most important outcomes of thermodynamics – most notably, the laws of thermodynamics – as conclusions from derivations in statistical physics. Special emphasis is on subjects that are vital to engineering education. These include, first of all, quantum statistics, like the Fermi-Dirac distribution, as well as diffusion processes, both of which are fundamental to a sound understanding of semiconductor devices. Another important issue for electrical engineering students is understanding of the mechanisms of noise generation and stochastic dynamics in physical systems, most notably in electric circuitry. Accordingly, the fluctuation-dissipation theorem of statistical mechanics, which is the theoretical basis for understanding thermal noise processes in systems, is presented from a signals-and-systems point of view, in a way that is readily accessible for engineering students and in relation with other courses in the electrical engineering curriculum, like courses on random processes.
Introductory Applied Quantum and Statistical Mechanics
Author: Peter L. Hagelstein
language: en
Publisher: John Wiley & Sons
Release Date: 2004-03-25
Dieses Lehrbuch der Quantenmechanik ist nicht für Physiker, sondern vorrangig für Elektroingenieure und Materialwissenschaftler gedacht. Entsprechend werden die theoretischen Konzepte durch praxisrelevante Beispiele, etwa aus der Halbleiterherstellung oder der Entwicklung von Quantencomputern, illustriert. Mit durchgearbeiteten Beispielen und Kontrollfragen für das Selbststudium; ein Lösungsheft ist erhältlich.
Introduction to Applied Statistical Signal Analysis
Introduction to Applied Statistical Signal Analysis, Third Edition, is designed for the experienced individual with a basic background in mathematics, science, and computer. With this predisposed knowledge, the reader will coast through the practical introduction and move on to signal analysis techniques, commonly used in a broad range of engineering areas such as biomedical engineering, communications, geophysics, and speech. Topics presented include mathematical bases, requirements for estimation, and detailed quantitative examples for implementing techniques for classical signal analysis. This book includes over one hundred worked problems and real world applications. Many of the examples and exercises use measured signals, most of which are from the biomedical domain. The presentation style is designed for the upper level undergraduate or graduate student who needs a theoretical introduction to the basic principles of statistical modeling and the knowledge to implement them practically. Includes over one hundred worked problems and real world applications. Many of the examples and exercises in the book use measured signals, many from the biomedical domain.