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lecture_8

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Operations on matrices

We want to define operations on matrices: some (useful) ways of taking two matrices and making a new matrix.

Before we begin, a remark about $1\times 1$ matrices. These are of the form $[a_{11}]$ where $a_{11}$ is just a number. The square brackets $[\,]$ don't really matter here; they just keep the inside of a matrix in one place. So really: a $1\times 1$ matrix is just a number. This means that special cases of the operations we define will be operations on ordinary numbers. You should check that in the special case when all the matrices involved are $1\times 1$ matrices, the operations become the ordinary operations on numbers, so we are generalising the familiar operations (addition, subtraction, multiplication and so on) from numbers to matrices.

Matrix addition and subtraction

Definition of matrix addition

If $A$ and $B$ are matrices of the same size, then $A+B$ is defined to be the matrix with the same size as $A$ and $B$ so that the $(i,j)$ entry of $A+B$ is $a_{ij}+b_{ij}$, for every $i,j$.

If $A$ and $B$ are matrices of different sizes, then $A+B$ is undefined.

Example

\[ \begin{bmatrix}1&2&-2\\3&0&5\end{bmatrix}+\begin{bmatrix}-2&2&0\\1&1&1\end{bmatrix}=\begin{bmatrix}-1&4&-2\\4&1&6\end{bmatrix}.\]

Example

\[ \begin{bmatrix}1&2&-2\\3&0&5\end{bmatrix}+\begin{bmatrix}-2&2\\1&1\end{bmatrix}\text{ is undefined.}\]

Remarks

  1. For any matrices $A$ and $B$ with the same size: $A+B=B+A$. We say that matrix addition is commutative.
  2. For any matrices $A$, $B$ and $C$ with the same size: $(A+B)+C=A+(B+C)$. We say that matrix addition is associative.

Definition of the zero matrix

The $n\times m$ zero matrix is the $n\times m$ matrix so that every entry is $0$. We write this as $0_{n\times m}$. So \[ 0_{n\times m}=\begin{bmatrix} 0&0&\dots&0\\ 0&0&\dots&0\\ \vdots&\vdots&&\vdots\\ 0&0&\dots&0\end{bmatrix}\] where this matrix has $n$ rows and $m$ columns.

Exercise

Show that if $A$ is any $n\times m$ matrix, then \[ 0_{n\times m}+A=A=A+0_{n\times m}.\] Remember that when checking that matrices are equal, you have to check that they have the same size, and that all the entries are the same.

Definition of matrix subtraction

If $A$ and $B$ are matrices of the same size, then $A-B$ is defined to be the matrix with the same size as $A$ and $B$ so that the $(i,j)$ entry of $A-B$ is $a_{ij}-b_{ij}$, for every $i,j$.

If $A$ and $B$ are matrices of different sizes, then $A-B$ is undefined.

Example

\[ \begin{bmatrix}1&2&-2\\3&0&5\end{bmatrix}-\begin{bmatrix}-2&2&0\\1&1&1\end{bmatrix}=\begin{bmatrix}3&0&-2\\2&-1&4\end{bmatrix}.\]

Example

\[ \begin{bmatrix}1&2&-2\\3&0&5\end{bmatrix}-\begin{bmatrix}-2&2\\1&1\end{bmatrix}\text{ is undefined.}\]

Scalar multiplication

Definition of a scalar

In linear algebra, a scalar is just a fancy name for a number (in this course: a real number). The reason is that numbers are often used for scaling things up or down; for example, the scalar $3$ is often used to scale things up by a factor of $3$ (by multiplying by $3$).

Definition of scalar multiplication of matrices

If $c$ is a real number and $A$ is an $n\times m$ matrix, then we define the matrix $cA$ to be the $n\times m$ matrix given by multiplying every entry of $A$ by $c$. In other words, the $(i,j)$ entry of $cA$ is $ca_{i,j}$.

Example

If $A=\begin{bmatrix}1&0&-3\\3&-4&1\end{bmatrix}$, then $3A=\begin{bmatrix}3&0&-9\\9&-12&3\end{bmatrix}$. In other words, \[ 3\begin{bmatrix}1&0&-3\\3&-4&1\end{bmatrix}=\begin{bmatrix}3&0&-9\\9&-12&3\end{bmatrix}.\]

The negative of a matrix

We write $-A$ as a shorthand for $-1A$; so the $(i,j)$ entry of $-A$ is $-a_{ij}$. For example, \[ -\begin{bmatrix}-1&0&3\\3&-4&1\end{bmatrix}=\begin{bmatrix}1&0&-3\\-3&4&-1\end{bmatrix}.\]

Exercise

Prove that $A-B=A+(-B)$ for any matrices $A$ and $B$ of the same size.

lecture_8.1423737850.txt.gz · Last modified: by rupert

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