Numerical C: Applied Computational Programming with Case Studies

ISBN-13: 9781484250631 / Angielski / Miękka / 2019 / 312 str.

Philip Joyce

Spis treści

1. Introduction to C

2. Quadratic Formula

3. Integration by Trapezium Method

4. Monte Carlo Method of Integration

5. Matrices and Regression 

6. Product Moment Correlation Coefficient

7. Further Monte Carlo Methods

8. Augmented Matrix Method For Simultaneous Equations

9. Economic / Financial Programming Case Study

10. Another Case Study

A. Development Environment Reference

B. Syntax Reference

C. Answers to Exercises 

O autorze

Philip Joyce has 28 years experience as a software engineer – working on control of steel production, control of oil refineries, communications software (pre-Internet), office products (server software), and computer control of airports. Programming in Assembler, COBOL, Coral66, C, and C++. Mentor to new graduates in the company.  He also has a MSc in computational physics (including augmented matrix techniques and Monte Carlo techniques using Fortran) - Salford University 1996.   Chartered scientist, chartered physicist, member of the Institute of Physics (member of the higher education group).

Blurb

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.  

You will:

• 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