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MATLAB (an abbreviation of "MATrix LABoratory" [18]) is a proprietary multi-paradigm programming language and numeric computing environment 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.
BASIC (Beginners' All-purpose Symbolic Instruction Code) [1] is a family of general-purpose, high-level programming languages designed for ease of use. The original version was created by John G. Kemeny and Thomas E. Kurtz at Dartmouth College in 1963. They wanted to enable students in non-scientific fields to use computers.
Pages in category "Articles with example MATLAB/Octave code" The following 40 pages are in this category, out of 40 total. This list may not reflect recent changes. A.
A small piece of code in most general-purpose programming languages, this program is used to illustrate a language's basic syntax. Such program is often the first written by a student of a new programming language, [ 1 ] but such a program can also be used as a sanity check to ensure that the computer software intended to compile or run source ...
This is an accepted version of this page This is the latest accepted revision, reviewed on 14 February 2025. Language for communicating instructions to a machine The source code for a computer program in C. The gray lines are comments that explain the program to humans. When compiled and run, it will give the output "Hello, world!". A programming language is a system of notation for writing ...
These toolboxes provide APIs for the high-level and low-level implementation and use of many types of machine learning models that can integrate with the rest of the MATLAB ecosystem. These libraries also have support for code generation for embedded hardware. C++ is a compiled language that can interact with low-level hardware.
Octave (aka GNU Octave) is an alternative to MATLAB. Originally conceived in 1988 by John W. Eaton as a companion software for an undergraduate textbook, Eaton later opted to modify it into a more flexible tool. Development began in 1992 and the alpha version was released in 1993. Subsequently, version 1.0 was released a year after that in 1994.
In applied mathematics, test functions, known as artificial landscapes, are useful to evaluate characteristics of optimization algorithms, such as convergence rate, precision, robustness and general performance.