Book

Numerical Methods Using MATLAB

by John H. Mathews, Kurtis D. Fink

📖 Overview

Numerical Methods Using MATLAB provides a comprehensive introduction to computational mathematics and numerical analysis using MATLAB as the programming environment. The text covers core topics including root-finding, interpolation, numerical integration, and differential equations. The authors present mathematical concepts alongside practical implementation details and MATLAB code examples. Each chapter contains exercises and programming projects that reinforce the material through hands-on application. This text serves as both a theoretical foundation in numerical methods and a practical guide to solving mathematical problems computationally. The combination of mathematical rigor with applied programming makes it relevant for students in engineering, mathematics, and scientific computing. The book emphasizes the interplay between mathematical theory and computational practice, demonstrating how abstract concepts translate into concrete problem-solving tools. Its approach bridges pure mathematics with real-world applications through systematic algorithm development and implementation.

👀 Reviews

Readers find this textbook clear and practical for learning numerical methods, though some note it requires prior MATLAB familiarity. Likes: - Well-organized chapters with progressive difficulty - Detailed examples and exercises with MATLAB code - Strong coverage of interpolation and numerical integration - Helpful chapter summaries and review questions Dislikes: - Several typos and errors in problem solutions - Code examples could be more optimized/efficient - Limited coverage of certain advanced topics - High price point for students Ratings: Amazon: 3.9/5 (43 reviews) Goodreads: 3.8/5 (24 ratings) Specific Comments: "The step-by-step explanations helped me understand complex algorithms" - Amazon reviewer "Some MATLAB code is outdated and could use more vectorization" - Engineering student on Reddit "Good for teaching but expensive for what you get" - Goodreads review "Problems at chapter ends need better solutions" - Math professor on MathOverflow

📚 Similar books

Numerical Methods for Scientific Computing by Daniel Kaplan This textbook combines MATLAB implementations with theoretical foundations of numerical analysis and includes extensive code examples for common computational problems.

Applied Numerical Linear Algebra by James W. Demmel This work connects practical MATLAB programming with the mathematical principles of numerical linear algebra through step-by-step algorithm implementations.

Scientific Computing with MATLAB by Dingyu Xue and YangQuan Chen The text presents numerical methods through MATLAB code implementations while focusing on engineering applications and practical problem-solving strategies.

Numerical Computing with MATLAB by Cleve Moler This book, written by the creator of MATLAB, provides fundamental algorithms and numerical methods with direct implementations in MATLAB code.

Essential MATLAB for Engineers and Scientists by Brian Hahn and Daniel Valentine The text covers numerical methods and MATLAB programming through engineering and scientific computing examples with complete code implementations.

🤔 Interesting facts

🔢 The book has remained a cornerstone text in numerical methods education since its first edition in 1999, evolving through four editions to keep pace with MATLAB's developments. 🧮 Author John H. Mathews pioneered the integration of computer programming into mathematics education, starting in the 1970s when computers were just beginning to enter classrooms. 💻 MATLAB, the programming language featured in the book, was originally created to give students access to LINPACK and EISPACK without having to learn Fortran. 📚 The text uniquely combines theoretical mathematical concepts with practical computer implementation, featuring over 200 MATLAB programs that readers can directly use or modify. 🎓 Co-author Kurtis Fink developed many of the book's problem sets while teaching at California State University, where he noticed students learned numerical methods more effectively when theory was immediately followed by hands-on programming.