10 Best Matlab Books [Updated 2023]
MATLAB is one of the most popular platforms scientists and engineers use to develop engineering models, algorithms, and data analysis. MATLAB includes an environment capable of designing procedures and iterative analysis purposes tuned with a computer programming language for directly expressing array mathematics and matrix. This software tool comes with a Live Editor that can be used for developing scripts by combining formatted texts, codes, and output.
Key Highlights
- You can learn to use this powerful language to solve complex problems and create sophisticated applications.
- Well-suited for numerical methods, which are essential in scientific and engineering applications.
- You can gain practical skills directly applicable to your field by reading these books.
List of Top 10 Matlab books
To have a better understanding of MATLAB, have a look at the top 10 Matlab books.
| Sr.no | Books | Author | Published |
Rating (out of 5) |
| 1 | Engineering Programming – C, Matlab, and Java: In C, Matlab, and Java | M Austin, D. Chancogne | 11 Jan 1999 | Amazon: 4.7 |
| 2 | Robust Control Design with MATLAB | Da-Wei Gu, Mihail M Konstantinov, Petko H. Petkov | 8 May 2013 | Amazon: 4.5 |
| 3 | Getting Started with MATLAB | Rudra Pratap | 1 Jan 2019 | Amazon: 4.3 |
| 4 | Digital Image Processing Using MATLAB | Ralph Gonzalez, Richard Woods, Steven Eddins | 1 Jul 2017 | Amazon: 4.4 |
| 5 | MATLAB: An Introduction with Applications | Amos Gilat | 21 Nov 2016 | Amazon: 4.5 |
| 6 | Beginning MATLAB and Simulink | Sulaymon Eshkabilov | 4 Nov 2022 | Amazon: 5.0 |
| 7 | MATLAB for Machine Learning | Giuseppe Ciaburro | 28 Aug 2017 | Amazon: 4.2 |
| 8 | Matlab Deep Learning | Phil Kim | 1 Jan 2016 | Amazon: 4.2 |
| 9 | Computational Partial Differential Equations Using MATLAB | Jichun Li, Yi-Tung Chen | 14 Oct 2019 | Amazon: 4.6 |
| 10 | Programming in MATLAB | Ram N Patel, Ankush Mittal | Amazon: 4.4 |
Let us discuss the reviews and takeaways of the Matlab books:-
Book #1. Engineering Programming – C, Matlab, and Java: In C, Matlab, and Java
Author: M. Austin, D. Chancogne
Book Review
Are you interested in learning MATLAB for your job? This book is the perfect reference guide to make things fall into the right places. There are four tutorials present that cover MATLAB through the eyes of C and Java. Filled with examples, this book serves big times for students trying to strengthen their expertise in MATLAB.
Key Takeaways
- Includes simple procedures to solve the matrix programs.
- Compares the importance of MATLAB when computing modern engineering problems.
- Covers topics like dynamic memory allocation, program control, expressions and operators, and basic data types.
- Explains Java programs with easy examples
Book #2: Robust Control Design with MATLAB
Author: Da-Wei Gu, Mihail M Konstantinov, Petko H. Petkov
Book Review
“Robust Control Design with MATLAB” is a comprehensive guide to the theory and practice of robust control design using MATLAB. Written by Da-Wei Gu, Mihail M Konstantinov, and Petko H. Petkov, all experts in control systems engineering.
This book encompasses a diverse array of subjects associated with robust control design, which includes:
- Introduction to robust control design and its importance in modern engineering applications
- Mathematical tools and techniques for robust control design, including Lyapunov functions, H-infinity control, and mu-synthesis
- Robust stability analysis and performance assessment
- Design of powerful controllers for linear and nonlinear systems
- Practical implementation issues, such as controller tuning and implementation constraints
Key Takeaways
- Explained complex concepts in a way that is easy to understand, even for readers with limited experience in control systems engineering.
- Mathematical tools and techniques, such as Lyapunov functions and H-infinity control, are used in robust control design to ensure system stability and performance.
- The authors provide abundant examples and case studies demonstrating how robust control design can be applied in real-world engineering applications.
Book #3: Getting Started with MATLAB
Author: Rudra Pratap
Book Review
This book on MATLAB allows readers to get accustomed to the subject through examples and illustrations. One of the core competencies of this book is its emphasis on hands-on learning. The author provides numerous examples and exercises throughout the book, allowing readers to practice and reinforce their understanding of the concepts. This latest edition covers differential equations, regression and analysis, and algebraic equations. For beginners, this is a handy book to start with.
Key Takeaways
- Covers different scripts and functions using MATLAB
- Filled with a rich set of examples and illustrations
- A separate chapter dedicated to differential equations
Book #4: Digital Image Processing Using MATLAB
Author: Ralph Gonzalez, Richard Woods, Steven Eddins
Book Review
For those developing their career in MATLAB, this book is a must-have. This book covers in detail the different image processing fundamentals using MATLAB. It covers all the key topics focusing on Digital Image Processing. It also covers key concepts of the Image Processing Toolbox and guides users towards using it by developing new codes.
Key Takeaways
- Covers all the key topics with precise detailing
- Creates a link between DIP and MATLAB toolbox through examples
- Handles complicated issues and jargon with ease.
Book #5: MATLAB: An Introduction with Applications
Author: Amos Gilat
Book Review
This book offers a perfect guiding tool for those who are into technical computing and want to learn MATLAB. This book introduces the readers to different aspects of MATLAB and provides an in-depth analysis of the tool, from the core basics to advanced topics.
Key Takeaways
- Covers the basics and advanced areas with precise detailing
- Offers link to online access for keynotes and takeaways
- Very robust volume and covers most areas.
Book #6: Beginning MATLAB and Simulink
Author: Sulaymon Eshkabilov
Book Review
“Beginning MATLAB and Simulink” is an introductory guide to MATLAB and Simulink, two widely-used software tools for scientific and engineering applications. Sulaymon Eshkabilov, an assistant professor at the National University of Uzbekistan, writes the book. The book covers the basics of MATLAB and Simulink, including:
- Introduction to MATLAB and its various features, such as data types, operators, and functions
- Basics of programming in MATLAB, including control structures and user-defined functions
- Working with matrices and arrays in MATLAB
- Introduction to Simulink and its various features, such as modeling and simulation of dynamic systems
- Building and simulating Simulink models for multiple applications, including mechanical, electrical, and control systems
Key Takeaways
- Helps users learn Simulink and MATLAB through several models and examples
- NUMERICAL ROOT methods are explained through clear methods
- Users can use Simulink and MATLAB for different data science projects
Book #7: MATLAB for Machine Learning
Author: Giuseppe Ciaburro
Book Review
“MATLAB for Machine Learning” is an excellent resource for anyone interested in using MATLAB for machine learning applications. This book thoroughly introduces the theory and practice of machine learning using MATLAB. The author explains complex concepts in a way that is easy to understand, making the book accessible to readers with limited machine learning or programming experience.
Key Takeaways
- Uncovers several procedures of data transformation using SAS EXPORT/IMPORT tools
- Defines different correlations, regression techniques, and OLS estimation
- Deals with classification methods
- Covers Decision Trees and Naïve Bayes Algorithm
Book #8: Matlab Deep Learning
Author: Phil Kim
Book Review
“Matlab Deep Learning” is an excellent resource for anyone interested in using MATLAB for deep learning applications. This book is an in-depth introduction to the theory and practice of deep learning using MATLAB, making it suitable for students, researchers, and practicing engineers. The content is well-written and includes a variety of examples and case studies to help readers develop practical skills in deep learning.
Key Takeaways
- Introduction to deep learning and its various applications
- Basics of MATLAB programming, including data types, operators, and functions
- Working with data in MATLAB, including data preprocessing and feature selection
- Neural network architectures, such as feedforward networks, CNNs( convolutional neural networks), and RNNs(recurrent neural networks)
- Advanced deep learning techniques, such as transfer learning and generative adversarial networks (GANs)
Book #9: Computational Partial Differential Equations Using MATLAB
Author: Jichun Li, Yi-Tung Chen
Book Review
“Computational Partial Differential Equations Using MATLAB” is a Worthwhile resource for individuals who want to gain knowledge and skills in the field of computational partial differential equations, PDEs, and their applications using MATLAB. Jichun Li and Yi-Tung Chen, experts in computational mathematics, wrote them. The book is comprehensive, and well-written and provides numerous examples and case studies to help readers develop practical skills in PDE computation.
Key Takeaways
- Finite difference methods for solving PDEs, including forward, backward, and central differences
- Finite element methods for solving PDEs, including continuous Galerkin and discontinuous Galerkin methods
- Spectral methods for solving PDEs, including Fourier and Chebyshev methods
- Numerical methods for solving nonlinear PDEs, such as Newton’s method and the method of lines
Book #10: Programming in MATLAB
Author: Ram N Patel, Ankush Mittal
Book Review
This book will cater primarily to scientists and engineers interested in learning MATLAB. The primary goal of this book is to develop programming skills among those with no prior experience in MATLAB programming. Plenty of examples are provided for readers to observe and understand.
Key Takeaway
- Working with matrices and arrays in MATLAB
- Plotting and visualization in MATLAB
- Introduction to object-oriented programming in MATLAB
- Advanced topics in MATLAB programming, such as numerical methods and optimization techniques
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