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Titlebook: Applied Scientific Computing; With Python Peter R. Turner,Thomas Arildsen,Kathleen Kavanagh Textbook 2018 Springer International Publishing

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發(fā)表于 2025-3-21 17:38:34 | 只看該作者 |倒序瀏覽 |閱讀模式
期刊全稱Applied Scientific Computing
期刊簡稱With Python
影響因子2023Peter R. Turner,Thomas Arildsen,Kathleen Kavanagh
視頻videohttp://file.papertrans.cn/161/160129/160129.mp4
發(fā)行地址Provides practical programming examples and exercises in the increasingly popular, free and open-source Python language.Presents a project-oriented approach that helps readers practice the introduced
學科分類Texts in Computer Science
圖書封面Titlebook: Applied Scientific Computing; With Python Peter R. Turner,Thomas Arildsen,Kathleen Kavanagh Textbook 2018 Springer International Publishing
影響因子.This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through simple-to-follow examples using Python..Topics and features: provides an accessible and applications-oriented approach, supported by working Python code for many of the methods; encourages both problem- and project-based learning through extensive examples, exercises, and projects drawn from practical applications; introduces the main concepts in modeling, python programming, number representation, and errors; explains the essential details of numerical calculus, linear, and nonlinear equations, including the multivariable Newton method; discusses interpolation and the numerical solution of differential equations, covering polynomial interpolation, splines, and the Euler, Runge–Kutta, and shooting methods; presents largely self-contained cha
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沙發(fā)
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Numerical Calculus,e similar to those of numerical integration, in that they are typically based on using (in this case, differentiating) an interpolation polynomial. One major and important difference between numerical approaches to integration and differentiation is that integration is numerically a highly satisfact
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Iterative Solution of Nonlinear Equations,e iterative in nature. We begin with perhaps the simplest idea – using bisection to reduce an interval which we know contains a solution to an acceptable tolerance. Next, we then present Newton’s method which is based on where the tangent line at a particular point would cross the axis. Provided we
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Interpolation,to use our knowledge of solving linear systems of equations to find the Lagrange interpolation polynomial by solving the Vandermonde system for the coefficients. However that is both inefficient and because of ill-conditioning subject to computational error. The use of the Lagrange basis polynomials
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1868-0941 riented approach that helps readers practice the introduced .This easy-to-understand textbook presents a modern approach to learning numerical methods (or scientific computing), with a unique focus on the modeling and applications of the mathematical content. Emphasis is placed on the need for, and
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Textbook 2018ing and applications of the mathematical content. Emphasis is placed on the need for, and methods of, scientific computing for a range of different types of problems, supplying the evidence and justification to motivate the reader. Practical guidance on coding the methods is also provided, through s
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