Essential MATLAB for Engineers and Scientists, Seventh Edition, provides a concise, balanced overview of MATLAB's functionality, covering both fundamentals and applications. The essentials are illustrated throughout, featuring complete coverage of the software's windows and menus. Program design and algorithm development are presented, along with many examples from a wide range of familiar scientific and engineering areas. This edition has been updated to include the latest MATLAB versions through 2018b. This is an ideal book for a first course on MATLAB, but is also ideal for an engineering problem-solving course using MATLAB.
- Updated to include all the newer features through MATLAB R2018b
- Includes new chapter on useful toolboxes
- Provides additional examples on engineering applications
|Edition description:||7th ed.|
|Product dimensions:||7.40(w) x 9.40(h) x 1.00(d)|
About the Author
Brian Hahn was a professor in the Department of Mathematics and Applied Mathematics at the University of Cape Town. In his career, Brian wrote more than 10 books for teaching programming languages to beginners.Daniel T. Valentine is Professor Emeritus and was Professor and Chair of the Department of Mechanical and Aeronautical Engineering, Clarkson University, Potsdam, New York. He was also Affiliate Director of the Clarkson Space Grant Program of the New York NASA Space Grant Consortium, a program that provided support for undergraduate and graduate research. His Ph.D. degree is in fluid Mechanics from the Catholic University of America. His BS and MS degrees in mechanical engineering are from Rutgers University.
Table of Contents
1. Introduction 2. MATLAB Fundamentals 3. Program Design and Algorithm Development 4. MATLAB Functions and Data Import-Export Utilities 5. Logical Vectors 6. Matrices and Arrays 7. Function M-files 8. Loops 9. MATLAB Graphics 10. Vectors as Arrays and other Data Structures 11. Dynamical Systems 12. Simulation 13. Introduction to Numerical Methods 14. Signal Processing 15. SIMULINK® Toolbox 16. Symbolics Toolbox 17. Complex Variables Applications