Here I want to write about the usage of matrices and vectors, for which the language is optimized and which can be used very conveniently.

A matrix is defined in square brackets, entries of one row are separated by comma, rows by semicolon, so for example:

*A = [1, 2; 3, 4]*

Vectors of course are only special cases of matrices, namely one-dimensional ones. Thus they can be defined via

*V1 = [1, 2]*(row vector) or

*V2 = [3;4]*(column vector) - in the following I will only use the term matrix.

There are different predefined Matlab function for creating certain matrices: Here I want to mention

*ones()*,

*zeros()*and

*rand()*.

*ones(a, b)*creates a

*a x b*matrix (

*a*rows,

*b*columns)

*with all entries a 1. This can also be done for higher dimensions, if only one parameter is passed over a 2-dimensional square matrix is created.*

*zeros()*and

*rand()*do the same,

*zeros()*fills the resulting matrix with zeros,

*rand()*with random entries between 0 and 1.

With matrices we can calculate as we are used to. Via +, -, * we can do matrix addition, subtraction and multiplication. * is overloaded and can also be used for a scalar multiplication between a scalar (a number) and a matrix.

In the Matlab documentation all possible functions regarding matrices are listed, like for example determining the rank (

*rank()*) and and and.

Another intesting function when using matrices is the extraction of submatrices.

We can define a submatrix of the matrix A consisting of the rows

*a*to

*b*and columns

*c*to

*d*as follows:

*A(a:b, c:d)*

When emitting the colon the dimension is taken completely:

*A(:, c:d)*

Via the function

*sum()*we thus can for example conveniently sum over the rows / colums of a matrix, for row

*i*the command for this is:

*sum(A(1,:))*

In the next post I will show another interesting application, there we describe the solving of equation systems.

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Thanks for your kind words, always very nice to hear!

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