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Course: Precalculus > Unit 7
Lesson 5: Properties of matrix addition & scalar multiplicationProperties of matrix addition
Learn about the properties of matrix addition (like the commutative property) and how they relate to real number addition.
In the table below, , , and are matrices of equal dimensions.
Property | Example |
---|---|
Commutative property of addition | |
Associative property of addition | |
Additive identity property | For any matrix |
Additive inverse property | For each |
Closure property of addition |
This article explores these matrix addition properties.
Matrices and matrix addition
A matrix is a rectangular arrangement of numbers into rows and columns. The dimensions of a matrix give the number of rows and columns of the matrix in that order. Since matrix has rows and columns, it is called a matrix.
To add two matrices of the same dimensions, simply add the entries in the corresponding positions.
If any of this is new to you, you should check out the following articles before you proceed:
Dimensions considerations
Notice that the sum of two matrices is another matrix. In general, the sum of two matrices is another matrix. This describes the closure property of matrix addition.
If the dimensions of two matrices are not the same, the addition is not defined. This is because if is a matrix and is a matrix, then some entries in matrix will not have corresponding entries in matrix !
Matrix addition & real number addition
Because matrix addition relies heavily on the addition of real numbers, many of the addition properties that we know to be true with real numbers are also true with matrices.
Let's take a look at each property individually.
Commutative property of addition:
This property states that you can add two matrices in any order and get the same result.
This parallels the commutative property of addition for real numbers. For example, .
The following example illustrates this matrix property.
Notice how the commutative property of addition for matrices holds thanks to the commutative property of addition for real numbers!
Associative property of addition:
This property states that you can change the grouping in matrix addition and get the same result. For example, you can add matrix to first, and then add matrix , or, you can add matrix to , and then add this result to .
This property parallels the associative property of addition for real numbers. For example, .
Let's justify this matrix property by looking at an example.
In each column we simplified one side of the identity into a single matrix. The two resulting matrices are equivalent thanks to the real number associative property of addition. For example, .
Because of this property, we can write down an expression like and have this be completely defined. We do not need parentheses indicating which addition to perform first, as it doesn't matter!
Additive identity property:
A zero matrix, denoted , is a matrix in which all of the entries are .
Notice that when a zero matrix is added to any matrix , the result is always .
These examples illustrate what is meant by the additive identity property; that the sum of any matrix and the appropriate zero matrix is the matrix .
A zero matrix can be compared to the number zero in the real number system. For all real numbers , we know that . The number is the additive identity in the real number system just like is the additive identity for matrices.
Additive inverse property:
The opposite of a matrix is the matrix , where each element in this matrix is the opposite of the corresponding element in matrix .
For example, if , then .
If we add to we get a zero matrix, which illustrates the additive inverse property.
The sum of a real number and its opposite is always , and so the sum of any matrix and its opposite gives a zero matrix. Because of this, we refer to opposite matrices as additive inverses.
Check your understanding
For the problems below, let , , and be matrices.
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