MATLAB Training

MATLAB (matrix laboratory) is a multi-paradigm numerical computing environment. A proprietary programming language developed by MathWorks, MATLAB allows matrix manipulations, plotting of functions and data, implementation of algorithms, creation of user interfaces, and interfacing with programs written in other languages, including C, C++, C#, Java, Fortran and Python.

Although MATLAB is intended primarily for numerical computing, an optional toolbox uses the MuPAD symbolic engine, allowing access to symbolic computing abilities. An additional package, Simulink, adds graphical multi-domain simulation and model-based design for dynamic and embedded systems.

As of 2017, MATLAB has roughly 1 million users across industry and academia. MATLAB users come from various backgrounds of engineering, science, and economics.

MATLAB has several advantages over other methods or languages:

• Its basic data element is the matrix. A simple integer is considered an matrix of one row and one column.  Several mathematical operations that work on arrays or matrices are built-in to the Matlab environment. For example, cross-products, dot-products, determinants, inverse matrices.
• Vectorized operations. Adding two arrays together needs only one command, instead of a for or while loop.
• The graphical output is optimized for interaction. You can plot your data very easily, and then change colors, sizes, scales, etc, by using the graphical interactive tools.
• Matlab’s functionality can be greatly expanded by the addition of toolboxes. These are sets of specific functions that provided more specialized functionality. Ex: Excel link allows data to be written in a format recognized by Excel, Statistics Toolbox allows more specialized statistical manipulation of data (Anova, Basic Fits, etc)
• Matlab does not make for a great general purpose language. Matlab does scientific computing very well, but many other languages can take on a variety of tasks including web development, back end, and rich GUIs.
• Matlab is a semi-interpreted language compared to a compiled language (like C/C++). An interpreted language runs directly from the program code and need to be converted to machine code at each line of your program. Whereas, compiled languages are compiled into machine code, which typically runs more quickly than interpreted languages.
• Using Matlab can use a larger amount of RAM than a compiled program. For most applications, a typical computer will be fine. However, processing larger images, videos, or data sets may eat up a larger amount of memory.