Introduction to Scientific Computing with MATLAB® and Python Tutorials

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A01=Sheng Xu
Absolute Error
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Approximate Discrete Solution
Author_Sheng Xu
automatic-update
Buffon's Needle Problem
Category1=Non-Fiction
Category=PBKS
Category=PBW
Category=UB
Category=UMX
Category=UY
Category=UYM
computational mathematics
COP=United Kingdom
Definite Integral
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DP Number
eq_bestseller
eq_computing
eq_isMigrated=2
eq_nobargain
eq_non-fiction
error analysis methods
Euler's Method
Finite Difference Approximation
Finite Difference Method
Floating Point Representation
Horner's Method
initial boundary value problems
Language_English
linear algebra applications
LS Fit
LS Problem
LS Solution
LTE
Maclaurin Series
Monte Carlo Method
numerical analysis techniques
numerical methods
PA=Available
Parallel Computing
Price_€50 to €100
PS=Active
QR Decomposition
Relative Error
Roundoff Errors
scientific programming
softlaunch
Taylor Polynomial
Taylor Series Method
Taylor's Theorem
True Solution
undergraduate scientific computing course
Undetermined Coefficients

Product details

  • ISBN 9781032063188
  • Weight: 740g
  • Dimensions: 156 x 234mm
  • Publication Date: 26 Aug 2024
  • Publisher: Taylor & Francis Ltd
  • Publication City/Country: GB
  • Product Form: Paperback
  • Language: English
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This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing.

This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions.

•Where is the method applied?
•How is the method developed?
•How is the method implemented?
•How well does the method work?

The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.

Sheng Xu is an Associate Professor of Mathematics at Southern Methodist University in Dallas, TX. His research areas are in the field of fluid mechanics and scientific computing, with specialization in computational fluid dynamics (CFD). He has written a few CFD packages to simulate fluid-solid interactions using the immersed interface method.

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