This book is intended to introduce the reader to the practical calculation of feedback control circuits by examples of application. The material is presented in the order of the work necessary in the practical investigation of feedback control systems: analysis of the technical construction, setting up the equations, transformation into frequency notation, normalization, drawing of the system diagram and the Bode diagram, determination of the control system parameters and the behaviour in real time. Only an understanding of basic mathematics and of basic electricity is prerequisite. The book can be used for independent study, to serve the specialist as a reference book, and to offer the drive-system engineer a comprehensive presentation of the standard problems and solutions of drive-systems engineering. Although for the most part examples of drive systems will be used, the contents is presented in such an easy way that it can also be read by other than drive-system engineers.

The Bayesian Choice

Computers & Technology

Robert, Christian P.

Computer Science

Springer

This graduate-level textbook presents an introduction to Bayesian statistics and decision theory. Its scope covers both the basic ideas of statistical theory, and also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, the Stein effect, hierarchical and empirical Bayes modeling, Monte Carlo integration, and Gibbs sampling. It is the translation of a successful French text. In the translation to the English edition, the author has taken the opportunity to add and update material, and to include many problems and exercises for students. From reviews of the French edition: I strongly encourage everyone teaching Bayesian decision theory to use (this) as the main textbook. Journal of the American Statisical Association On the whole, the book serves its purpose admirably. Journal of the Royal Statistical Society

The Bayesian Choice: A Decision-Theoretic Motivation

Science & Math

Mathematics

Springer, Verlag

This Bayesian modeling book provides a self-contained entry to computational Bayesian statistics. Focusing on the most standard statistical models and backed up by real datasets and an all-inclusive R (CRAN) package called bayess, the book provides an operational methodology for conducting Bayesian inference, rather than focusing on its theoretical and philosophical justifications. 
Readers are empowered to participate in the real-life data analysis situations depicted here from the beginning. Special attention is paid to the derivation of prior distributions in each case and specific reference solutions are given for each of the models. Similarly, computational details are worked out to lead the reader towards an effective programming of the methods given in the book. In particular, all R codes are discussed with enough detail to make them readily understandable and expandable. 
Bayesian Essentials with R can be used as a textbook at both undergraduate and graduate levels. It is particularly useful with students in professional degree programs and scientists to analyze data the Bayesian way. The text will also enhance introductory courses on Bayesian statistics. Prerequisites for the book are an undergraduate background in probability and statistics, if not in Bayesian statistics.

Bayesian Essentials with R (Springer Texts in Statistics)

Marin, Jean-Michel

Software

An ideal text for applied statisticians needing a standalone introduction to computational Bayesian statistics, this work by a renowned authority on the subject focuses on standard models backed up by real datasets. It includes an inclusive R (CRAN) package.

This graduate-level textbook presents an introduction to Bayesian statistics and decision theory. Its scope covers both the basic ideas of statistical theory, but also some of the more modern and advanced topics of Bayesian statistics such as complete class theorems, Stein effects, hierarchical and empirical modelling, and Gibbs sampling. It is the translation of a successful French text. In the translation to the English edition, the author has taken the opportunity to add and update material, and to include many problems and exercises for students.

The Bayesian Choice: A Decision-Theoretic Motivation (Springer Texts in Statistics)

In the 1990s, optical technology and photonics industry developed fast, but further progress became difficult due to a fundamental limit of light known as the diffraction limit. This limit could be overcome using the novel technology of nano-optics or nanophotonics in which the size of the electromagnetic field is decreased down to the nanoscale and is used as a carrier for signal transmission, processing, and fabrication. Such a decrease beyond the diffraction limit is possible by using optical near-fields. The true nature of nano-optics and nanophotonics involves not only their abilities to meet the above requirements but also their abilities to realize qualitative innovations in photonic devices, fabrication techniques, energy conversion and information processing systems. The objective of this work is to review the innovations of optical science and technology by nano-optics and nanophotonics. While in conventional optical science and technology, light and matter are discussed separately, in nano-optics and nanophotonics, light and matter have to be regarded as being coupled to each other, and the energy flow between nanoparticles is bidirectional. This means that nano-optics and nanophotonics have to be regarded as a technology fusing optical fields and matter. This unique work reviews and covers the most recent topics of nano-optics, applications to device operations, fabrication techniques, energy conversion, information processing, architectures and algorithms. Each chapter is written by the leading scientists in the relevant field. Thus, this work will provide high-quality scientific and technical information to scientists, engineers, and graduate students who are and will be engaged in R&D of nano-optics and nanophotonics. Especially, the topics to be covered by this work will be popularly used by the engineers in the rapidly growing market of the optical energy conversion.

Networking & Cloud Computing

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Books by Robert, Christian P.

See the best price to sell, buy, or rent books by Robert, Christian P.. BookScouter helps to compare book prices from 25+ online bookstores and 30+ buyback vendors with a single search.

The Bayesian Choice

The Bayesian Choice: A Decision-Theoretic Motivation

Bayesian Essentials with R (Springer Texts in Statistics)

The Bayesian Choice: A Decision-Theoretic Motivation

Bayesian Essentials with R (Springer Texts in Statistics)

The Bayesian Choice: A Decision-Theoretic Motivation (Springer Texts in Statistics)

Bayesian Essentials with R (Springer Texts in Statistics)