Introduction

MATLAB, an abbreviation for “Matrix Laboratory,” is a high-level computer language and an interactive environment used by engineers and scientists worldwide. It was developed by MathWorks and first released in the mid-1980s. MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, the creation of user interfaces, and intercommunication with programs written in other languages. The platform was created to provide an easy and efficient environment for numerical computation, visualization, and programming. With its built-in mathematical functions, MATLAB became popular among engineers and scientists for technical computing. The capabilities of this language have expanded over time to include data analysis, development of algorithms, modeling, simulation, and prototyping. The MATLAB ecosystem has significantly expanded its capabilities, allowing for specialized applications in fields such as signal processing, image and video processing, control systems, test and measurement, computational finance, and computational biology. Among these toolboxes, Simulink, a MATLAB-based graphical programming environment for modeling, simulating, and analyzing multidomain dynamical systems, stands out for its impact on various engineering fields. Thus, this language has been instrumental in shaping the way complex mathematical problems are approached and solved in various industries. Obviously, one of its primary advantages is the ease with which users can express computational mathematics. The platform is particularly popular among engineers and scientists for its robust toolboxes that simplify tasks such as signal processing, image analysis, and control systems design, among others. Another strong point of MATLAB is its rich library of built-in functions for both numerical analysis and symbolic computations. Thus, as the reader will witness in the chapters below, the MATLAB environment is highly optimized for matrix operations, which makes it particularly efficient for problems and algorithms that are matrix and vector-based. However, MATLAB can be considered less efficient for general-purpose programming due to its relatively slow execution speed for certain types of tasks, especially when compared to compiled languages like C or Fortran. It is also proprietary software, which may limit its accessibility to individuals or institutions on a tight budget, as the cost of licenses can be prohibitive. The syntax and functionality of MATLAB are unique, and while this is an advantage in its specific context, it can be a disadvantage for users who need to integrate or migrate to different programming environments, as the portability of MATLAB code to other computer languages is not straightforward.