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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.
FreeMat is a free open-source numerical computing environment and programming language, [1] similar to MATLAB and GNU Octave. [2] In addition to supporting many MATLAB functions and some IDL functionality, it features a codeless interface to external C, C++, and Fortran code, further parallel distributed algorithm development (via MPI), and has plotting and 3D visualization capabilities. [3]
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GNU Octave is a scientific programming language for scientific computing and numerical computation.Octave helps in solving linear and nonlinear problems numerically, and for performing other numerical experiments using a language that is mostly compatible with MATLAB.
A MEX file is a type of computer file that provides an interface between MATLAB or Octave and functions written in C, C++ or Fortran.It stands for "MATLAB executable". When compiled, MEX files are dynamically loaded and allow external functions to be invoked from within MATLAB or Octave as if they were built-in functions.
A delimited text file is a text file used to store data, in which each line represents a single book, company, or other thing, and each line has fields separated by the delimiter. [3] Compared to the kind of flat file that uses spaces to force every field to the same width, a delimited file has the advantage of allowing field values of any length.
A computer simulation (or "sim") is an attempt to model a real-life or hypothetical situation on a computer so that it can be studied to see how the system works. By changing variables in the simulation, predictions may be made about the behaviour of the system. It is a tool to virtually investigate the behaviour of the system under study.
The two methods are also compared in Figure 3, created by Matlab simulation. The contours are lines of constant ratio of the times it takes to perform both methods. When the overlap-add method is faster, the ratio exceeds 1, and ratios as high as 3 are seen. Fig 3: Gain of the overlap-add method compared to a single, large circular convolution.