Cantitate/Preț
Produs

Introduction to Scientific Computing and Data Analysis: Texts in Computational Science and Engineering, cartea 13

Autor Mark H. Holmes
en Limba Engleză Paperback – 31 mai 2018
This textbook provides and introduction to numerical computing and its applications in science and engineering.  The topics covered include those usually found in an introductory course, as well as those that arise in data analysis.  This includes optimization and regression based methods using a singular value decomposition.  The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science.  The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used.  The MATLAB codes used to produce most of the figures and data tables in the text are available on the author’s website and SpringerLink.
Citește tot Restrânge

Toate formatele și edițiile

Toate formatele și edițiile Preț Express
Paperback (2) 45905 lei  3-5 săpt.
  Springer International Publishing – 12 iul 2024 45905 lei  3-5 săpt.
  Springer International Publishing – 31 mai 2018 52087 lei  38-44 zile
Hardback (1) 52072 lei  38-44 zile
  Springer International Publishing – 12 iul 2023 52072 lei  38-44 zile

Din seria Texts in Computational Science and Engineering

Preț: 52087 lei

Nou

Puncte Express: 781

Preț estimativ în valută:
9216 10736$ 8048£

Carte tipărită la comandă

Livrare economică 13-19 ianuarie 26

Preluare comenzi: 021 569.72.76

Specificații

ISBN-13: 9783319807621
ISBN-10: 3319807625
Pagini: 497
Ilustrații: XIV, 497 p. 177 illus., 138 illus. in color.
Dimensiuni: 155 x 235 mm
Greutate: 0.73 kg
Ediția:Softcover reprint of the original 1st ed. 2016
Editura: Springer International Publishing
Colecția Springer
Seria Texts in Computational Science and Engineering

Locul publicării:Cham, Switzerland

Cuprins

Introduction to Scientific Computing.- Solving a Nonlinear Equation.- Matrix Equations.- Eigenvalue Problems.- Interpolation.- Numerical Integration.- Initial Value Problems.- Optimization.- Data Analysis.- Appendices.

Recenzii

“The material is accompanied by many examples, exercises, as well as diagrams and tables of resulting data which are produced by MATLAB for which the programs are available on the author's website. The book is intended for beginners in scientific computing with basic knowledge in calculus, matrix algebra, and differential equations. … a good reading for the more advanced scientific engineer or lecturer in this field who may find numerous suggestions for working or teaching.” (Gudula Rünger, zbMATH 1368.65002, 2017)

Notă biografică

Mark Holmes is a Professor at Rensselaer Polytechnic Institute.  His current research interests include mechanoreception and sleep-wake cycles. Professor Holmes has three published books in Springer's Texts in Applied Mathematics series: Introduction to Perturbation Methods, Introduction to the Foundations of Applied Mathematics, and Introduction to Numerical Methods in Differential Equations.

Textul de pe ultima copertă

This textbook provides and introduction to numerical computing and its applications in science and engineering.  The topics covered include those usually found in an introductory course, as well as those that arise in data analysis.  This includes optimization and regression based methods using a singular value decomposition.  The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science.  The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used.  The MATLAB codes used to produce most of the figures and data tables in the text are available on the author’s website and SpringerLink.


Caracteristici

MATLAB codes used for all of the numerical methods are available from author's website Extensive coverage of optimization methods including regression, both principal and independent component analysis, and variational calculus Directed towards problem solving that incorporates the mathematical foundations of the subject Includes supplementary material: sn.pub/extras