Skip to content

Mathematics · Ch 3 — Matrices

Types of Matrices

3.3

Types of Matrices

3.3 Types of Matrices

Matrices come in several forms, each defined by its shape or the pattern of its entries. Different operations and properties apply to different kinds, so we examine each type, from the simplest shapes to matrices with special internal structure.

Column Matrix

A matrix with exactly one column is called a column matrix; with mm rows its order is m×1m \times 1.

A=[03−112]A = \begin{bmatrix} 0 \\ 3 \\ -1 \\ \frac{1}{2} \end{bmatrix}

is a column matrix of order 4×14 \times 1. In general notation, A=[aij]m×1A = [a_{ij}]_{m \times 1}.

Note

A column matrix is also called a column vector. Every column of any matrix is itself a column matrix.

Row Matrix

A matrix with exactly one row is called a row matrix; with nn columns its order is 1×n1 \times n.

B=[14−152]1×4B = \begin{bmatrix} 1 & 4 & -1 & \frac{5}{2} \end{bmatrix}_{1 \times 4}

is a row matrix. In general, B=[bij]1×nB = [b_{ij}]_{1 \times n}.

Square Matrix

A matrix is a square matrix when the number of rows equals the number of columns. If m=nm = n, it is square and said to be of order nn.

A=[3−10321−243]A = \begin{bmatrix} 3 & -1 & 0 \\ 3 & 2 & 1 \\ -2 & 4 & 3 \end{bmatrix}

is a square matrix of order 3. In general, A=[aij]m×mA = [a_{ij}]_{m \times m} or simply [aij]n[a_{ij}]_{n}.

The Diagonal of a Square Matrix

If A=[aij]A = [a_{ij}] is square of order nn, the elements a11,a22,a33,…,anna_{11}, a_{22}, a_{33}, \dots, a_{nn} — those where the row number equals the column number — constitute the diagonal (or principal/main diagonal) of the matrix.

For

A=[13−124−1356],A = \begin{bmatrix} 1 & 3 & -1 \\ 2 & 4 & -1 \\ 3 & 5 & 6 \end{bmatrix},

the diagonal elements are a11=1a_{11} = 1, a22=4a_{22} = 4, and a33=6a_{33} = 6.

Important

Only square matrices have a diagonal. For a rectangular matrix (m≠nm \neq n), the concept does not apply in the same way.

Diagonal Matrix

A square matrix B=[bij]m×mB = [b_{ij}]_{m \times m} is a diagonal matrix if all non-diagonal elements are zero:

bij=0wheneveri≠j.b_{ij} = 0 \quad \text{whenever} \quad i \neq j.

The diagonal elements themselves may be zero or non-zero; what matters is that every off-diagonal entry is zero.

Examples:

  • Order 1: A=[4]A = [4]
  • Order 2: B=[−1002]B = \begin{bmatrix} -1 & 0 \\ 0 & 2 \end{bmatrix}
  • Order 3: C=[−1.100020003]C = \begin{bmatrix} -1.1 & 0 & 0 \\ 0 & 2 & 0 \\ 0 & 0 & 3 \end{bmatrix}
Watch out

A diagonal matrix must be square. The definition explicitly requires a square matrix.

Scalar Matrix

A diagonal matrix whose diagonal elements are all equal is called a scalar matrix. That is, a square matrix B=[bij]n×nB = [b_{ij}]_{n \times n} with:

  • bij=0b_{ij} = 0 when i≠ji \neq j (it is diagonal), and
  • bij=kb_{ij} = k when i=ji = j, for some constant kk.

Examples:

  • Order 1: A=[3]A = [3] (here k=3k = 3)
  • Order 2: B=[−100−1]B = \begin{bmatrix} -1 & 0 \\ 0 & -1 \end{bmatrix} (here k=−1k = -1)
  • Order 3: C=[300030003]C = \begin{bmatrix} 3 & 0 & 0 \\ 0 & 3 & 0 \\ 0 & 0 & 3 \end{bmatrix} (here k=3k = 3)
Note

Multiplying any matrix by a scalar matrix of appropriate order has the same effect as multiplying by the scalar kk — hence the name.

Identity Matrix

A square matrix in which all diagonal elements are 1 and all non-diagonal elements are 0 is called an identity matrix:

aij={1if i=j,0if i≠j.a_{ij} = \begin{cases} 1 & \text{if } i = j, \\ 0 & \text{if } i \neq j. \end{cases}

The identity matrix of order nn is denoted InI_n, or simply II when the order is clear.

Examples:

  • Order 1: I1=[1]I_1 = [1]
  • Order 2: I2=[1001]I_2 = \begin{bmatrix} 1 & 0 \\ 0 & 1 \end{bmatrix}
  • Order 3: I3=[100010001]I_3 = \begin{bmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix}
Important

The identity matrix is a scalar matrix with k=1k = 1. Every identity matrix is a scalar matrix, but a scalar matrix is an identity matrix only when k=1k = 1. …