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Titre : Data Analysis : Statistical and Computational Methods for Scientists and Engineers Type de document : Monographie Auteurs : Siegmund Brandt, Auteur Editeur : Springer International Publishing Année de publication : 2014 Importance : 532 p. ISBN/ISSN/EAN : 978-3-319-03762-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Statistiques
[Termes IGN] analyse de variance
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode des moindres carrés
[Termes IGN] méthode du maximum de vraisemblance (estimation)
[Termes IGN] probabilités
[Termes IGN] régression
[Termes IGN] série temporelle
[Termes IGN] statistiques
[Termes IGN] variable aléatoireRésumé : (éditeur) The fourth edition of this successful textbook presents a comprehensive introduction to statistical and numerical methods for the evaluation of empirical and experimental data. Equal weight is given to statistical theory and practical problems. The concise mathematical treatment of the subject matter is illustrated by many examples, and for the present edition a library of Java programs has been developed. It comprises methods of numerical data analysis and graphical representation as well as many example programs and solutions to programming problems. The programs (source code, Java classes, and documentation) and extensive appendices to the main text are available for free download from the book’s page at www.springer.com.
Contents: Probabilities. Random variables. Random numbers and the Monte Carlo Method. Statistical distributions (binomial, Gauss, Poisson). Samples. Statistical tests. Maximum Likelihood. Least Squares. Regression. Minimization. Analysis of Variance. Time series analysis.
Audience: The book is conceived both as an introduction and as a work of reference. In particular it addresses itself to students, scientists and practitioners in science and engineering as a help in the analysis of their data in laboratory courses, working for bachelor or master degrees, in thesis work, and in research and professional work.Note de contenu : 1- Introduction
2- Probabilities
3- Random Variables: Distributions
4- Computer Generated Random Numbers: The Monte Carlo Method
5- Some Important Distributions and Theorems
6- Samples
7- The Method of Maximum Likelihood
8- Testing Statistical Hypotheses
9- The Method of Least Squares
10- Function Minimization
11- Analysis of Variance
12- Linear and Polynomial Regression
13- Time Series AnalysisNuméro de notice : 25778 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Monographie En ligne : https://doi.org/10.1007/978-3-319-03762-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94973
Titre : Introduction to partial differential equations Type de document : Guide/Manuel Auteurs : Peter J. Olver, Auteur Editeur : Springer International Publishing Année de publication : 2014 Importance : 636 p. Format : 18 x 26 cm ISBN/ISSN/EAN : 978-3-319-02099-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse mathématique
[Termes IGN] équation de Laplace
[Termes IGN] équation de Poisson
[Termes IGN] équation différentielle
[Termes IGN] équation linéaire
[Termes IGN] équation non linéaire
[Termes IGN] équation polynomiale
[Termes IGN] fonction de Green
[Termes IGN] principe de Huygens
[Termes IGN] transformation de Fourier
[Termes IGN] valeur limiteRésumé : (auteur) This textbook is designed for a one year course covering the fundamentals of partial differential equations, geared towards advanced undergraduates and beginning graduate students in mathematics, science, engineering, and elsewhere. The exposition carefully balances solution techniques, mathematical rigor, and significant applications, all illustrated by numerous examples. Extensive exercise sets appear at the end of almost every subsection, and include straightforward computational problems to develop and reinforce new techniques and results, details on theoretical developments and proofs, challenging projects both computational and conceptual, and supplementary material that motivates the student to delve further into the subject.
No previous experience with the subject of partial differential equations or Fourier theory is assumed, the main prerequisites being undergraduate calculus, both one- and multi-variable, ordinary differential equations, and basic linear algebra. While the classical topics of separation of variables, Fourier analysis, boundary value problems, Green's functions, and special functions continue to form the core of an introductory course, the inclusion of nonlinear equations, shock wave dynamics, symmetry and similarity, the Maximum Principle, financial models, dispersion and solitons, Huygens'
Principle, quantum mechanical systems, and more make this text well attuned to recent developments and trends in this active field of contemporary research. Numerical approximation schemes are an important component of any introductory course, and the text covers the two most basic approaches: finite differences and finite elements.Note de contenu : 1- What Are Partial Differential Equations?
2- Linear and Nonlinear Waves
3- Fourier Series
4- Separation of Variables
5- Finite Differences
6- Generalized Functions and Green’s Functions
7- Fourier Transforms
8- Linear and Nonlinear Evolution Equations
9- A General Framework for Linear Partial Differential Equations
10- Finite Elements and Weak Solutions
11- Dynamics of Planar Media
12- Partial Differential Equations in SpaceNuméro de notice : 25874 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Manuel DOI : 10.1007/978-3-319-02099-0 En ligne : https://doi.org/10.1007/978-3-319-02099-0 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95568
Titre : The Python workbook : a brief introduction with exercises and solutions Type de document : Guide/Manuel Auteurs : Ben Stephenson, Auteur Editeur : Springer International Publishing Année de publication : 2014 Importance : 165 p. ISBN/ISSN/EAN : 978-3-319-14240-1 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Langages informatiques
[Termes IGN] programmation informatique
[Termes IGN] Python (langage de programmation)Résumé : (Editeur) While other textbooks devote their pages to explaining introductory programming concepts, This book focuses exclusively on exercises, following the philosophy that computer programming is a skill best learned through experience and practice. Designed to support and encourage hands-on learning about programming, this student-friendly work contains 174 exercises, spanning a variety of academic disciplines and everyday situations. Solutions to selected exercises are also provided, supported by brief annotations that explain the technique used to solve the problem, or highlight specific points of Python syntax. No background knowledge is required to solve the exercises, beyond the material covered in a typical introductory Python programming course. Note de contenu :
1. EXERCISES
1.1 Introduction to Programming Exercises
1.2 If Statement Exercises
1.3 Loop Exercises
1.4 Function Exercises
1.5 List Exercises
1.6 Dictionary Exercises
1.7 File and Exception Exercises
1.8 Recursion Exercises
2. SOLUTIONS
2.1 Introduction to Programming Solutions
2.2 If Statement Solutions
2.3 Loop Solutions
2.4 Function Solutions
2.5 List Solutions
2.6 Dictionary Solutions
2.7 File and Exception Solutions
2.8 Recursion SolutionsNuméro de notice : 26279 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE Nature : Manuel informatique DOI : 10.1007/978-3-319-14240-1 En ligne : https://doi.org/10.1007/978-3-319-14240-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94929
Titre : Computational Physics Type de document : Guide/Manuel Auteurs : Philipp Scherer, Auteur Editeur : Springer International Publishing Année de publication : 2013 Importance : 454 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-319-00401-3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Physique
[Termes IGN] collocation
[Termes IGN] dynamique des fluides
[Termes IGN] équation linéaire
[Termes IGN] interpolation
[Termes IGN] Java (langage de programmation)
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] problème du voyageur de commerce
[Termes IGN] quantum (physique)
[Termes IGN] thermodynamique
[Termes IGN] transformation de Fourier
[Termes IGN] trigonométrieRésumé : (éditeur) This textbook presents basic and advanced computational physics in a very didactic style. It contains very-well-presented and simple mathematical descriptions of many of the most important algorithms used in computational physics. The first part of the book discusses the basic numerical methods. The second part concentrates on simulation of classical and quantum systems. Several classes of integration methods are discussed including not only the standard Euler and Runge Kutta method but also multi-step methods and the class of Verlet methods, which is introduced by studying the motion in Liouville space. A general chapter on the numerical treatment of differential equations provides methods of finite differences, finite volumes, finite elements and boundary elements together with spectral methods and weighted residual based methods. The book gives simple but non trivial examples from a broad range of physical topics trying to give the reader insight into not only the numerical treatment but also simulated problems. Different methods are compared with regard to their stability and efficiency. The exercises in the book are realised as computer experiments. Note de contenu : I- Numerical Methods
II- Simulation of Classical and Quantum SystemsNuméro de notice : 25827 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Manuel En ligne : https://doi.org/10.1007/978-3-319-00401-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95121
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Titre : Discrete & computational geometry Type de document : Périodique Editeur : Springer International Publishing Année de publication : 1986 - ISBN/ISSN/EAN : 0179-5376 Note générale : 1986-2014 accessibles sur ISTEX Langues : Anglais (eng) Descripteur : [Termes IGN] géomètrie algorithmique Numéro de notice : 130 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE Nature : Titre de périodique En ligne : https://link.springer.com/journal/volumesAndIssues/454 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87112