Introduction to MATLAB for Engineers and Scientists

Solutions for Numerical Computation and Modeling
1. Auflage 2017
ISBN: 978-1-4842-3188-3
Verlag: Apress

Buch, Englisch, 213 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 3577 g

Familiarize yourself with MATLAB using this concise, practical tutorial that is focused on writing code to learn concepts. Starting from the basics, this book covers array-based computing, plotting and working with files, numerical computation formalism, and the primary concepts of approximations. Introduction to MATLAB is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation.
In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you’ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts. 

What You'll Learn - Apply sample code to your engineering or science problems

- Work with MATLAB arrays, functions, and loops 

- Use MATLAB’s plotting functions for data visualization

- Solve numerical computing and computational engineering problems with a MATLAB case study

Who This Book Is For
Engineers, scientists, researchers, and students who are new to MATLAB. Some prior programming experience would be helpful but not required.

Autoren/Hrsg.

Nagar, Sandeep

Fachgebiete

• Mathematik | Informatik EDV | Informatik Programmierung | Softwareentwicklung Programmier- und Skriptsprachen
• Mathematik | Informatik Mathematik Numerik und Wissenschaftliches Rechnen Computeranwendungen in der Mathematik
• Mathematik | Informatik EDV | Informatik Business Application Mathematische & Statistische Software
• Technische Wissenschaften Technik Allgemein Mathematik für Ingenieure
• Mathematik | Informatik EDV | Informatik Informatik Mathematik für Informatiker

Inhaltsverzeichnis

1. Introduction.- 2. Working with Arrays.- 3. Plotting.- 4. Data Accessibility and Persistence.- 5. Functions and loops.- 6. Numerical Computing.- 7. A Numerical Computation Case Study.

Über Autor(innen)

Sandeep Nagar, Ph.D. teaches and consults on the use of Python and other open source programming languages for for data science/analysis and numerical computing for engineering and science applications. In addition to teaching at universities, he frequently gives workshops covering open source software.  Sandeep has a Ph.D. in Material Science from KTH, Sweden in May 2012. Prior to that degree, he obtained a M.Sc. in Physics with specialization in Electronics and Radio Physics and a B.Sc.B.Ed degrees in India.