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Practical Numerical and Scientific Computing with MATLAB® and Python by Eihab B. M. Bashier (2020, Hardcover)
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- Sofort-KaufenPraktisches numerisches und wissenschaftliches Rechnen mit MATLAB und Python von Eihab B.M
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Über dieses Produkt
Product Identifiers
PublisherCRC Press LLC
ISBN-100367076691
ISBN-139780367076696
eBay Product ID (ePID)3038301133
Product Key Features
Number of Pages330 Pages
LanguageEnglish
Publication NamePractical Numerical and Scientific Computing with Matlab® and Python
Publication Year2020
SubjectProgramming / Games, Programming Languages / General, General, Arithmetic
TypeTextbook
AuthorEihab B. M. Bashier
Subject AreaMathematics, Computers, Science
FormatHardcover
Dimensions
Item Weight28.4 Oz
Item Length9.2 in
Item Width6.1 in
Additional Product Features
Intended AudienceCollege Audience
LCCN2019-052363
IllustratedYes
Table Of ContentSolving Linear Systems. Ill-conditioning and Regularization Techniques in solutions of linear systems. Solving a system of nonlinear equations. Solving the Eigenvalue Problem. Data Interpolation. Numerical Differentiation and Integration. Solving Systems of Linear Ordinary Differential Equations. Solving Systems of Nonlinear Ordinary Differential Equations. Non-standard Finite Difference Methods for Solving ODEs. Solving Optimization Problems: Linear Programming. Solving Optimization Problems: Nonlinear Programming. Solving Dynamical Optimization Problems
SynopsisThis book concentrates on the practical aspects of numerical analysis and linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python. Although the book focuses on the approximation problem rather than on error analysis of mathematical problems, it provides practical ways to calculate errors. The book is divided into three parts, covering topics in numerical linear algebra, methods of interpolation, numerical differentiation and integration, solutions of differential equations, linear and non-linear programming problems, and optimal control problems. This book has the following advantages: It adopts the programming languages, MATLAB and Python, which are widely used among academics, scientists, and engineers, for ease of use and contain many libraries covering many scientific and engineering fields. It contains topics that are rarely found in other numerical analysis books, such as ill-conditioned linear systems and methods of regularization to stabilize their solutions, nonstandard finite differences methods for solutions of ordinary differential equations, and the computations of the optimal controls. It provides a practical explanation of how to apply these topics using MATLAB and Python. It discusses software libraries to solve mathematical problems, such as software Gekko, pulp, and pyomo. These libraries use Python for solutions to differential equations and static and dynamic optimization problems. Most programs in the book can be applied in versions prior to MATLAB 2017b and Python 3.7.4 without the need to modify these programs. This book is aimed at newcomers and middle-level students, as well as members of the scientific community who are interested in solving math problems using MATLAB or Python., Practical Numerical and Scientific Computing with MATLAB(R) and Python concentrates on the practical aspects of numerical analysis and linear and non-linear programming. It discusses the methods for solving different types of mathematical problems using MATLAB and Python. Although the book focuses on the approximation problem rather than on error analysis of mathematical problems, it provides practical ways to calculate errors. The book is divided into three parts, covering topics in numerical linear algebra, methods of interpolation, numerical differentiation and integration, solutions of differential equations, linear and non-linear programming problems, and optimal control problems. This book has the following advantages: It adopts the programming languages, MATLAB and Python, which are widely used among academics, scientists, and engineers, for ease of use and contain many libraries covering many scientific and engineering fields. It contains topics that are rarely found in other numerical analysis books, such as ill-conditioned linear systems and methods of regularization to stabilize their solutions, nonstandard finite differences methods for solutions of ordinary differential equations, and the computations of the optimal controls. It provides a practical explanation of how to apply these topics using MATLAB and Python. It discusses software libraries to solve mathematical problems, such as software Gekko, pulp, and pyomo. These libraries use Python for solutions to differential equations and static and dynamic optimization problems. Most programs in the book can be applied in versions prior to MATLAB 2017b and Python 3.7.4 without the need to modify these programs. This book is aimed at newcomers and middle-level students, as well as members of the scientific community who are interested in solving math problems using MATLAB or Python.
LC Classification NumberQ183.9B375 2020
