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Numerical C : applied computational programming with case studies /

Learn applied numerical computing using the C programming language, starting with a quick primer on the C programming language and its SDK. This book then dives into progressively more complex applied math formula for computational methods using C with examples throughout and a larger, more complete...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Joyce, Philip (Software engineer)
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berkeley, CA : Apress, 2019.
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 1 0 |a Numerical C :  |b applied computational programming with case studies /  |c Philip Joyce. 
260 |a Berkeley, CA :  |b Apress,  |c 2019. 
300 |a 1 online resource (319 pages) 
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504 |a Includes bibliographical references and index. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed October 1, 2019). 
505 0 |a Intro; Table of Contents; About the Author; About the Technical Reviewer; Acknowledgments; Introduction; Chapter 1: Introduction to C; First Program; Get and Print a Character; Add Two Numbers; Add Two Decimal Numbers; Multiply Two Numbers; Divide Two Numbers; Forloops; Flowcharts; Do Loops; Switch Instruction; If Then Else; If Then Else If; Data Arrays; Functions; Strings; Mathematical Functions; Structures; Size of Variables; Goto Command; Common Mathematical and Logical Symbols; Chapter 2: Solving Equations; Quadratic Equations; Factorizing; Completing the Square; Quadratic Formula 
505 8 |a Equations of Higher PowersTrial and Improvement; Which Solution Are We Finding?; Three Solutions; User-Entered Function; Chapter 3: Numerical Integration; Trapezium Integration; Simplification of Formula; Inverse Power; Combined Powers; Problem with Negative Areas; Simpson's Rule Integration; Chapter 4: Monte Carlo Integration; Finding an Odd-Shaped Area; Monte Carlo Area of Graph; Area of a Circle; Higher Dimension Graphs; Even Higher Dimensions; Chapter 5: Matrices; Matrix Arithmetic; Matrix Addition and Subtraction; Matrix Multiplication; Matrix Inverse; Coding a Matrix Inverse 
505 8 |a Testing the CodeChapter 6: Correlation and PMCC; Scatter Graphs and Correlation; Product Moment Correlation Coefficient; Chapter 7: Monte Carlo Methods; Radioactive Decay Simulation; Buffon's Needle; Random Walk; Chapter 8: Augmented Matrix; Manual Solution to Simultaneous Equations; Augmented Matrix Program; Twelve Simultaneous Equations; Chapter 9: File Access; First Program to Write a File; Writing a Large Data File; Medical Records File; Company Records File; Chapter 10: Differential Equations; Taylor and Maclaurin Series; Euler Method; Runge-Kutta Method 
505 8 |a Second Order Differential EquationsAppendix A: Development Environment Reference; Visual Studio; Command Line; Appendix B: Syntax Reference; Mathematical Functions; Pointers; Standard Library Functions; Comparing Double, Float, and Integer; Appendix C: Answers to Problems; Index 
520 |a Learn applied numerical computing using the C programming language, starting with a quick primer on the C programming language and its SDK. This book then dives into progressively more complex applied math formula for computational methods using C with examples throughout and a larger, more complete application towards the end. Numerical C starts with the quadratic formula for finding solutions to algebraic equations that model things such as price vs. demand or rise vs. run or slip and more. Later in the book, you'll work on the augmented matrix method for simultaneous equations. You'll also cover Monte Carlo method model objects that could arise naturally as part of the modeling of a real-life system, such as a complex road network, the transport of neutrons, or the evolution of the stock market. Furthermore, the Monte Carlo method of integration examines the area under a curve including rendering or ray tracing and the shading in a region. Furthermore, you'll work with the product moment correlation coefficient: correlation is a technique for investigating the relationship between two quantitative, continuous variables, for example, age and blood pressure. By the end of the book, you'll have a feeling for what computer software could do to help you in your work and apply some of the methods learned directly to your work. What You Will Learn Gain software and C programming basics Write software to solve applied, computational mathematics problems Create programs to solve equations and calculus problems Use the trapezium method, Monte Carlo method, line of best fit, product moment correlation coefficient, Simpson's rule, and matrix solutions Write code to solve differential equations Apply one or more of the methods to an application case study Who This Book Is For Those with an existing knowledge of rudimentary mathematics (school level) and some basic programming experience. This is also important to people who may work in mathematics or other areas (for example, life sciences, engineering, or economics) and need to learn C programming. 
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