{"id":4861,"date":"2021-08-31T17:47:40","date_gmt":"2021-08-31T17:47:40","guid":{"rendered":"https:\/\/mathemerize.com\/?p=4861"},"modified":"2022-01-16T17:01:09","modified_gmt":"2022-01-16T11:31:09","slug":"different-types-of-matrices","status":"publish","type":"post","link":"https:\/\/mathemerize.com\/different-types-of-matrices\/","title":{"rendered":"Different Types of Matrices – Definitions and Examples"},"content":{"rendered":"
Here you will what is matrix and definitions of different types of matrices with examples.<\/p>\n
Let’s begin –<\/p>\n
A set of mn numbers (real or imaginary) arranged in the form of a rectangular array of m rows and n columns is called an m \\(\\times\\) n matrix (to be read as m by n matrix).<\/p>\n
A m by n matrix is usually written as<\/p>\n
A = \\(\\begin{bmatrix}a_{11} & a_{12} & …… & a_{1n} \\\\ a_{21} & a_{22} & …… & a_{2n}\\\\ . & . & . \\\\ a_{m1} & a_{m2} & …… & a_{mn} \\end{bmatrix}\\)<\/p>\n
All different types of matrices with examples are given below :<\/p>\n
A matrix having only one row is called a row matrix or a row-vector.<\/p>\n
Example : A = [ 1 2 -1 2 ] is a row matrix of order \\(1 \\times 4\\).<\/p>\n
A matrix having only one column is called a column matrix or a column vector.<\/p>\n
Example : \\(\\begin{bmatrix} 1 \\\\ 2 \\\\ -1 \\end{bmatrix}\\) is a column matrix of order \\(3 \\times 1\\).<\/p>\n
A matrix in which number of rows is equal to the number of columns, say n, is called a square matrix of order n.<\/p>\n
Example : the matrix \\(\\begin{bmatrix} 2 & 1 & -1 \\\\ 3 & -2 & 5 \\\\ 1 & 5 & -3 \\end{bmatrix}\\) is a square matrix of order \\(3 \\times 3\\) in which diagonal elements are 2, -2 and -3.<\/p>\n
A square matrix A = \\([a_{ij}]_{n\\times n}\\) is called a diagonal matrix if all the elements, except those in the leading diagonal are zero.<\/p>\n
Example : the matrix \\(\\begin{bmatrix} 1 & 0 & 0 \\\\ 0 & 2 & 0 \\\\ 0 & 0 & 3 \\end{bmatrix}\\) is a diagonal denoted by A = diag [1, 2, 3].<\/p>\n
A square matrix A = \\([a_{ij}]_{n\\times n}\\) is called a scalar matrix if<\/p>\n
(i) \\(a_{ij}\\) = 0 for all i \\(\\ne\\) j and,<\/p>\n
(ii) \\(a_{ii}\\) = c, for all i, where c \\(\\ne\\) 0<\/p>\n
In other words, a diagonal matrix in which all the diagonal elements are equal is called the scalar matrix.<\/p>\n
Example : the matrix \\(\\begin{bmatrix} 2 & 0 \\\\ 0 & 2 \\end{bmatrix}\\) is scalar martix of order 2.<\/p>\n
A square matrix A = \\([a_{ij}]_{n\\times n}\\) is called a identity or unit matrix if<\/p>\n
(i) \\(a_{ij}\\) = 0 for all i \\(\\ne\\) j and,<\/p>\n
(ii) \\(a_{ii}\\) = 1, for all i<\/p>\n
In other words, a diagonal matrix in which all the diagonal elements is unity is called the unit matrix.<\/p>\n
The identity matrix of order n is denoted by \\(I_n\\).<\/p>\n
Example : the matrix \\(I_2\\) = \\(\\begin{bmatrix} 1 & 0 \\\\ 0 & 1 \\end{bmatrix}\\) is identity matrix of order 2.<\/p>\n
A matrix in which al elements are zero is called a null or a zero matrix,<\/p>\n
Example : the matrix \\(\\begin{bmatrix} 0 & 0 \\\\ 0 & 0 \\end{bmatrix}\\) is null matrix of order 2.<\/p>\n
A square matrix A = \\([a_{ij}]\\) is called an upper triangular matrix if \\(a_{ij}\\) = 0 for all i > j.<\/p>\n
Thus, in an upper triangular matrix, all elements below the main diagonal are zero.<\/p>\n
Example : \\(\\begin{bmatrix} 1 & 3 & 4 \\\\ 0 & 4 & 5 \\\\ 0 & 0 & 7 \\end{bmatrix}\\) is a upper triangular matrix.<\/p>\n
A square matrix A = \\([a_{ij}]\\) is called an lower triangular matrix if \\(a_{ij}\\) = 0 for all i < j.<\/p>\n
Thus, in an lower triangular matrix, all elements above the main diagonal are zero.<\/p>\n
Example : \\(\\begin{bmatrix} 1 & 0 & 0 \\\\ 2 & 3 & 0 \\\\ 1 & 6 & 5 \\end{bmatrix}\\) is a lower triangular matrix.<\/p>\n\n\n