Programming with MATLAB for Scientists: A Beginner’s Introduction by Eugeniy E. Mikhailov

This book offers an introduction to the basics of MATLAB programming to scientists and engineers. The author leads with engaging examples to build a working knowledge, specifically geared to those with science and engineering backgrounds. The reader is empowered to model and simulate real systems, as well as present and analyze everyday data sets. In order to achieve those goals, the contents bypass excessive "under the hood" details, and instead gets right down to the essential, practical foundations for successful programming and modelling. Readers will benefit from the following features:

• Teaches programming to scientists and engineers using a problem-based approach, leading with illustrative and interesting examples.
• Emphasizes a hands-on approach, with "must-know" information and minimal technical details.
• Utilizes examples from science and engineering to showcase the application of learned concepts on real problems.
• Showcases modelling of real systems, gradually advancing from simpler to more challenging problems.
• Highlights the practical uses of data processing and analysis in everyday life.

Buy: Programming with MATLAB for Scientists: A Beginner’s Introduction Hardcover – Import, 1 Feb 2018 by Eugeniy E. Mikhailov (Author)

PDF: Programming with MATLAB for Scientists: A Beginner’s Introduction by Randy Moore in Computer Science on October 21, 2019

Book Description

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This book offers an introduction to the basics of MATLAB programming to scientists and engineers. The author leads with engaging examples to build a working knowledge, specifically geared to those with science and engineering backgrounds.

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Contents

I Computing Essentials

1 Computers and Programming Languages: An Introduction

2 MATLAB Basics

3 Boolean Algebra, Conditional Statements, Loops

4 Functions, Scripts, and Good Programming Practice

II Solving Everyday Problems with MATLAB

5 Solving Systems of Linear Algebraic Equations.

6 Fitting and Data Reduction

7 Numerical Derivative

8 Root Finding Algorithms

9 Numerical Integration Methods

10 Data Interpolation

III Going Deeper and Expanding the Scientist’s Toolbox

11 Random Number Generators and Random Processes

12 Monte Carlo Simulations .

13 The Optimization Problem

14 Ordinary Differential Equations

15 Discrete Fourier-Transform

16 Digital Filters.