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Systems of Equations (Simultaneous Equations)
Gaussian Elimination
Gaussian eliminiation can be used when the number of unknown variables you have is equal to the number of equations you are given.
I’m pretty sure it’s the name for the method you use to solve simultaneous equations in school.
For example if you have 1 equation and 1 unknown:
Number of Solutions
Let’s generalise the example above to
There are 3 possible cases:
2x2 Systems
A 2x2 system is one with 2 equations and 2 unknown variables.
Example 1
We’ve essentially created a 1x1 system for and now that’s solved we can back substitute it into equation (1) (or equation (2), it doesn’t matter) to work out the value of :
You can check the values for and are correct by substituting them into equation (2).
3x3 Systems
A 3x3 system is one with 3 equations and 3 unknown variables.
Example 1
The first step is to eliminate from (2) and (3) using (1):
This has created a 2x2 system of and which can be solved as any other 2x2 system. I’m too lazy to type up the working, but it is solved like any other 2x2 system.
These values can be back-substituted into any of the first 3 equations to find out :
Example 2
Eliminate from , :
We’ve created another 2x2 system of and
Eliminate from
We can see that can be any number, so there are infinite solutions. Let:
where can be any number
Substitute into :
Substitute and into :
Systems of Equations and Matrices
Many problems in engineering have a very large number of unknowns and equations to solve simultaneously. We can use matrices to solve these efficiently.
Take the following simultaneous equations::
They can be represented by the following matrices:
You can then express the system as:
A 3x3 System as a Matrix
Could be expressed in the form where:
An
System as a Matrix
Could be expressed in the form where:
Matrices
Order of a Matrix
The order of a matrix is its size e.g. or
Column Vectors
Column vectors are matrices with only one column:
Column vector variables typed up or printed are expressed in and when it is handwritten it is :
Matrix Algebra
Equality
Two matrices are the same if:
- Their order is the same
- Their corresponding elements are the same
Addition and Subtraction
Only possible if their order is the same.
Zero Matrix
This is a matrix whose elements are all zeros. For any matrix ,
We can only add matrices of the same order, therefore 0 must be of the same order as .
Multiplication
Let
To be able to multiply by , .
If , then does not exist.
When exists,
That is, is the ‘product’ of the th row of and th column of .
Multiplication of a Matrix by a Scalar
If is a scalar, we define
Example 1
Example 2
Other Properties of Matrix Algebra
In general, even if both exist
does not always mean or :
It follows that does not imply that as
and as and are not necessarily 0, is not necessarily equal to :
and
but
Special Matrices
Square Matrix
Where
Example 1
A
matrix.
Example 2
A
matrix.
Identity Matrix
The identity matrix is a square matrix whose eleements are all 0, except the leading diagonal which is 1s. The leading diagonal is the top left to bottom right corner.
It is usually denoted by or .
The identity matrix has the properties that
for any square matrix of the same order as I, and
for any vector .
Example 1
The
identity matrix.
Example 2
The
identity matrix.
Transposed Matrix
The transpose of matrix of order is matrix which has the order . It is found by reflecting it along the leading diagonal, or interchanging the rows and columns of .
Let matrix , then
Example 1
Example 2
Example 3
Orthogonal Matrices
A matrix, , such that
is said to be orthogonal.
Another way to say this is
Symmetric Matrices
A square matrix which is symmetric about its leading diagonal:
You can also express this as the matrix , where
is satisfied to all elements.
Example 1
Anti-Symmetric
A square matrix is anti-symmetric if
This can also be expressed as
This means that all elements on the leading diagonal must be 0.
Example 1
The Determinant
Determinant of a 2x2 System
The determinant of a system is
It is denoted by
A system of equations has a unique solution if
If , then there are either
- no solutions (the equations are inconsistent)
- intinitely many solutions
Determinant of a 3x3 System
Let
The matrices above are created by removing any elements on the same row or column as its corresponding coefficient:
Chessboard Determinant
may be obtained by expanding out any row or column. To figure out which coefficients should be subtracted and which ones added use the chessboard pattern of signs:
Properties of Determinants
If all elements of one row of a matrix are multiplied by a constant , the determinant of the new matrix is times the determinant of the original matrix:
This is also true if a column of a matrix is mutiplied by a constant.
Application if the fator appears in each elements of a row or column of a determinant it can be factored out
Application if all elements in one row or column of a matrix are zero, the value of the determinant is 0.
Application if is an matrix,
Swapping any two rows or columns of a matrix changes the sign of the determinant
Application If any two rows or two columns are identical, the determinant is zero.
Application If any row is a mutiple of another, or a column a multiple of another column, the determinant is zero.
The value of a determinant is unchanged by adding to any row a constant multiple of another row, or adding to any column a constant multiple of another column
If and are square matrices of the same order then
Inverse of a Matrix
If is a square matrix, then its inverse matrix is and is defined by the property that:
Not every matrix has an inverse
If the inverse exists, then it is very useful for solving systems of equations:
Therefore there must be a unique solution to : .
If then
Inverse of a 2x2 Matrix
If is the matrix
and its determinant, , satisfies , has the inverse given by
If , then matrix has no inverse.
Example 1
Find the inverse of matrix
.
Calculate the determinant
Since , the inverse exists.
Calculate
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