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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 number of approximation algorithms have been developed for the facility location problem and many of its variants. Without assumptions on the set of distances between clients and sites (in particular, without assuming that the distances satisfy the triangle inequality ), the problem is known as non-metric facility location and can be ...
When creating a MATLAB function, the name of the file should match the name of the first function in the file. Valid function names begin with an alphabetic character, and can contain letters, numbers, or underscores. Variables and functions are case sensitive. [44]
MATLAB Central currently houses around than 145,000 questions in its MATLAB Answers database. [24] The company actively supports numerous academic institutions to advance STEM education (primarily through the use of MathWorks products), including giving funding to MIT Open Courseware and MITx.
Octave programs consist of a list of function calls or a script. The syntax is matrix-based and provides various functions for matrix operations. It supports various data structures and allows object-oriented programming. [26] Its syntax is very similar to MATLAB, and careful programming of a script will allow it to run on both Octave and ...
Sigma function: Sums of powers of divisors of a given natural number. Euler's totient function: Number of numbers coprime to (and not bigger than) a given one. Prime-counting function: Number of primes less than or equal to a given number. Partition function: Order-independent count of ways to write a given positive integer as a sum of positive ...
A zero of a function f is a number x such that f(x) = 0. As, generally, the zeros of a function cannot be computed exactly nor expressed in closed form , root-finding algorithms provide approximations to zeros.
If, on the other hand, we know the characteristic function φ and want to find the corresponding distribution function, then one of the following inversion theorems can be used. Theorem. If the characteristic function φ X of a random variable X is integrable, then F X is absolutely continuous, and therefore X has a probability density function.