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Introduction to Numerical Programming

Titus A. Beu
€117.99
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A01=Titus A. Beu
advanced numerical algorithms for engineers
Ascending Sort
Author_Titus A. Beu
Birge-Vieta Method
Bubble Sort
C++
Canvas Coordinates
Canvas Widget
Category=UM
Cauchy Problem
Cholesky Factorization
computational physics applications
Crank Nicolson Difference Scheme
Cubic Spline Interpolation
Diagonalization of Matrices
differential equation solutions
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Euler's Method
Finite Difference Method
Gauss-Jordan Elimination
Gauss-Seidel Iterative Methods
Gaussian Quadratures
Horner's Scheme
Horner?S Scheme
Insertion Sort
Jacobi Method
Lagrange Interpolation Polynomial
Legendre Functions
Linear Congruential Generator
LU Decomposition
LU Factorization
Math Import
matrix computation strategies
Monte Carlo Method
Neville's Interpolation Method
Newton Cotes Formulas
Newton's Method
numerical analysis techniques
Numerov Method
Numerov's Method
Pivot Row
Programming
Programming Techniques In C
Python
Python Coding
Quicksort
Real Positive Definite Symmetric Matrix
Romberg's Method
Runge Kutta Method
Runge-Kutta Methods
scientific computing methods
Secant Method
Simpson's Rule
Solves Linear System
Solves Matrix Equation
stochastic simulation approaches
Symmetric Positive Definite
Taylor Series Method
The Canvas Widget
The Levenberg-Marquardt Method
The Newton-Cotes Quadrature Formulas
The Tkinter Package
Truncation Error
Velocity Verlet Method
Wave Packet

Product details

  • ISBN 9781466569676
  • Weight: 1150g
  • Dimensions: 178 x 254mm
  • Publication Date: 03 Sep 2014
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Paperback
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Description

Makes Numerical Programming More Accessible to a Wider Audience

Bearing in mind the evolution of modern programming, most specifically emergent programming languages that reflect modern practice, Numerical Programming: A Practical Guide for Scientists and Engineers Using Python and C/C++ utilizes the author’s many years of practical research and teaching experience to offer a systematic approach to relevant programming concepts. Adopting a practical, broad appeal, this user-friendly book offers guidance to anyone interested in using numerical programming to solve science and engineering problems. Emphasizing methods generally used in physics and engineering—from elementary methods to complex algorithms—it gradually incorporates algorithmic elements with increasing complexity.

Develop a Combination of Theoretical Knowledge, Efficient Analysis Skills, and Code Design Know-How

The book encourages algorithmic thinking, which is essential to numerical analysis. Establishing the fundamental numerical methods, application numerical behavior and graphical output needed to foster algorithmic reasoning, coding dexterity, and a scientific programming style, it enables readers to successfully navigate relevant algorithms, understand coding design, and develop efficient programming skills. The book incorporates real code, and includes examples and problem sets to assist in hands-on learning.

  • Begins with an overview on approximate numbers and programming in Python and C/C++, followed by discussion of basic sorting and indexing methods, as well as portable graphic functionality
  • Contains methods for function evaluation, solving algebraic and transcendental equations, systems of linear algebraic equations, ordinary differential equations, and eigenvalue problems
  • Addresses approximation of tabulated functions, regression, integration of one- and multi-dimensional functions by classical and Gaussian quadratures, Monte Carlo integration techniques, generation of random variables, discretization methods for ordinary and partial differential equations, and stability analysis

This text introduces platform-independent numerical programming using Python and C/C++, and appeals to advanced undergraduate and graduate students in natural sciences and engineering, researchers involved in scientific computing, and engineers carrying out applicative calculations.
About Titus A. Beu
Titus Adrian Beu , professor of theoretical and computational physics at the University Babes-Bolyai from Cluj-Napoca, Romania, has been active in the broader field of computational physics for more than 30 years. His research topics have evolved from Tokamak plasma and nuclear reactor calculations in the 1980s, collision theory and molecular cluster spectroscopy in the 1990s, to fullerenes and nanofluidics simulations in recent years. Development of ample computer codes has been at the core of all research projects the author has conducted. In parallel, he has lectured on general programming techniques and advanced numerical methods, general simulation methods, and advanced molecular dynamics.

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