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Matrix multiplication is thus a basic tool of linear algebra, and as such has numerous applications in many areas of mathematics, as well as in applied mathematics, statistics, physics, economics, and engineering. [3] [4] Computing matrix products is a central operation in all computational applications of linear algebra.
In computer science, Cannon's algorithm is a distributed algorithm for matrix multiplication for two-dimensional meshes first described in 1969 by Lynn Elliot Cannon. [1] [2]It is especially suitable for computers laid out in an N × N mesh. [3]
For example, if A is a 3-by-0 matrix and B is a 0-by-3 matrix, then AB is the 3-by-3 zero matrix corresponding to the null map from a 3-dimensional space V to itself, while BA is a 0-by-0 matrix. There is no common notation for empty matrices, but most computer algebra systems allow creating and computing with them.
As an example, we will find the Smith normal form of the following matrix over the integers. ( 2 4 4 − 6 6 12 10 4 16 ) {\displaystyle {\begin{pmatrix}2&4&4\\-6&6&12\\10&4&16\end{pmatrix}}} The following matrices are the intermediate steps as the algorithm is applied to the above matrix.
Here is a sample program that computes the factorial of an integer number from 2 to 69. For 5!, if "5 A" is pressed, it gives the result, 120. Unlike the SR-52 , the TI-58 and TI-59 do not have the factorial function built-in, but do support it through the software module which was delivered with the calculator.
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Multiplication of two matrices is defined if and only if the number of columns of the left matrix is the same as the number of rows of the right matrix. That is, if A is an m × n matrix and B is an s × p matrix, then n needs to be equal to s for the matrix product AB to be defined.