Finding the determinant using Cramer's method. Cramer's method for solving systems of linear equations. Let us calculate the main determinant of the system

Let a system of three be given linear equations:

To solve a system of linear equations using the Cramer method, the main determinant of the system  is compiled from the coefficients of the unknowns. For system (1), the main determinant has the form
.

Next, determinants for the variables are compiled
,,. To do this, in the main determinant, instead of a column of coefficients for the corresponding variable, a column of free terms is written, that is

,
,
.

Then the solution to the system is found using Cramer’s formulas

,
,

It should be noted that the system has a unique solution
, if the main determinant
. If
And
= 0,= 0,= 0, then the system has an infinite number of solutions, which cannot be found using Cramer’s formulas. If
And
0, or 0,or 0, then the system of equations is inconsistent, that is, it has no solutions.

Example

Solution:

1) Let’s compose and calculate the main determinant of the system, consisting of coefficients for the unknowns.

Therefore, the system has only decision.

2) Let's compose and calculate auxiliary determinants, replacing the corresponding column in  with a column of free terms.

Using Cramer's formulas we find the unknowns:

,
,
.

We'll check to make sure the decision is correct.

Those.
.

, i.e.

Answer: .

Example

Solve the system of equations using Cramer's method:

Solution:

1) Let’s compose and calculate the main determinant of the system from the coefficients of the unknowns:

Therefore, the system does not have a single solution.

2) Let’s compose and calculate auxiliary determinants, replacing the corresponding column in  with a column of free terms:

,
, therefore, the system is inconsistent.

Answer: the system is inconsistent.

Gauss method

The Gauss method consists of two stages. The first stage consists of sequentially eliminating variables from the equations of the system using actions that do not violate the equivalence of the system. For example, consider the first two equations of system (1).

(1)

It is necessary by adding these two equations to obtain an equation in which there is no variable . Let's multiply the first equation by , and the second on (
) and add the resulting equations

Let's replace the coefficient before y, z and free member on ,And Accordingly, we obtain a new pair of equations

Note that in the second equation there is no variable x.

Having carried out similar actions on the first and third equations of system (1), and then on the second and third equations obtained as a result of addition, we transform system (1) to the form

(2)

This result is possible if the system has a unique solution. In this case, the solution is found using the inverse of the Gaussian method (second stage). From the last equation of system (2) we find the unknown variable z, then from the second equation we find y, A x respectively from the first, substituting into them the already found unknowns.

Sometimes, as a result of adding two equations, the resulting equation can take one of the following forms:

A)
, Where
. This means that the system being solved is inconsistent.

B), that is
. Such an equation is excluded from the system; as a result, the number of equations in the system becomes less than the number of variables, and the system has an infinite number of solutions, the determination of which will be shown by example.

Example

Solution:

Let's consider the following way of implementing the first stage of the solution by the Gaussian method. Let us write down three lines of coefficients for unknowns and free terms corresponding to the three equations of the system. We separate the free terms from the coefficients with a vertical line, and draw a horizontal line under the third line.

We will circle the first line, which corresponds to the first equation of the system - the coefficients in this equation will remain unchanged. Instead of the second line (equation), you need to get a line (equation), where the coefficient for equal to zero. To do this, multiply all the numbers in the first line by (–2) and add them with the corresponding numbers in the second line. We write the resulting amounts under the horizontal line (fourth line). In order to, instead of the third line (equation), also obtain a line (equation) in which the coefficient at is equal to zero, multiply all the numbers in the first line by (–5) and add them with the corresponding numbers in the third line. We will write the resulting amounts in the fifth line and draw a new horizontal line under it. We will circle the fourth line (or the fifth, if you choose). The row with lower coefficients is selected. The coefficients in this line will remain unchanged. Instead of the fifth line, you need to get a line where two coefficients are already equal to zero. Multiply the fourth line by 3 and add it to the fifth. We write the amount under the horizontal line (sixth line) and circle it.

All described actions are depicted in Table 1 using arithmetic signs and arrows. We will write the lines circled in the table again in the form of equations (3) and, using the reverse of the Gauss method, we will find the values of the variables x, y And z.

Table 1

We restore the system of equations obtained as a result of our transformations:

(3)

Reverse Gaussian method

From the third equation
we find
.

Into the second equation of the system
substitute the found value
, we get
or
.

From the first equation
, substituting the already found values of the variables, we get
, that is
.

To ensure the correctness of the solution, the check must be done in all three equations of the system.

Examination:

, we get

We get

This means that the system is solved correctly.

Answer:
,
,
.

Example

Solve the system using the Gaussian method:

Solution:

The procedure for this example is similar to the previous example, and the specific steps are listed in Table 2.

As a result of the transformations, we obtain an equation of the form , therefore, the given system is inconsistent.

Answer: the system is inconsistent.

Example

Solve the system using the Gaussian method:

Solution:

Table 3

As a result of the transformations, we obtain an equation of the form , which is excluded from consideration. Thus, we have a system of equations in which the number of unknowns is 3, and the number of equations is 2.

The system has countless solutions. To find these solutions, we introduce one free variable. (The number of free variables is always equal to the difference between the number of unknowns and the number of equations remaining after transforming the system. In our case, 3 – 2 = 1).

Let
– free variable.

Then from the second equation we find
, where
, and then we find x from the first equation
or
.

Thus,
;
;
.

Let's check the equations that were not involved in finding And , that is, in the second and third equations of the original system.

Examination:

or , we get
.

The system is solved correctly. Giving an arbitrary constant different values, we will get different values x, y And z.

Answer:
;
;
.

Methods Kramer And Gauss- one of the most popular solution methods SLAU. In addition, in some cases it is advisable to use specific methods. The session is close, and now is the time to repeat or master them from scratch. Today we’ll look at the solution using Cramer’s method. After all, solving a system of linear equations using the Cramer method is a very useful skill.

Systems of linear algebraic equations

A system of linear algebraic equations is a system of equations of the form:

Value set x , in which the equations of the system turn into identities, is called a solution of the system, a And b are real coefficients. A simple system consisting of two equations with two unknowns can be solved in your head or by expressing one variable in terms of the other. But there can be much more than two variables (xes) in a SLAE, and here simple school manipulations are not enough. What to do? For example, solve SLAEs using Cramer's method!

So, let the system consist of n equations with n unknown.

Such a system can be rewritten in matrix form

Here A – the main matrix of the system, X And B , respectively, column matrices of unknown variables and free terms.

Solving SLAEs using Cramer's method

If the determinant of the main matrix is not equal to zero (the matrix is non-singular), the system can be solved using Cramer's method.

According to Cramer's method, the solution is found using the formulas:

Here delta is the determinant of the main matrix, and delta x nth – determinant obtained from the determinant of the main matrix by replacing the nth column with a column of free terms.

This is the whole essence of the Cramer method. Substituting the values found using the above formulas x into the desired system, we are convinced of the correctness (or vice versa) of our solution. To help you quickly grasp the essence, we give below an example of a detailed solution of SLAE using Cramer’s method:

Even if you don't succeed the first time, don't be discouraged! With a little practice, you will start cracking SLAUs like nuts. Moreover, now it is absolutely not necessary to pore over a notebook, solving cumbersome calculations and writing up the core. You can easily solve SLAEs using Cramer's method online, just by substituting the coefficients into the finished form. Try it online calculator Solutions using Cramer's method can be found, for example, on this website.

And if the system turns out to be stubborn and does not give up, you can always turn to our authors for help, for example, to buy a synopsis. If there are at least 100 unknowns in the system, we will definitely solve it correctly and on time!

This online calculator finds the solution to a system of linear equations (SLE) using the Cramer method. A detailed solution is given. To calculate, select the number of variables. Then enter the data into the cells and click on the "Calculate" button.

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Data entry instructions. Numbers are entered as integers (examples: 487, 5, -7623, etc.), decimals (ex. 67., 102.54, etc.) or fractions. The fraction must be entered in the form a/b, where a and b (b>0) are integers or decimal numbers. Examples 45/5, 6.6/76.4, -7/6.7, etc.

Cramer method

The Cramer method is a method for solving a quadratic system of linear equations with a nonzero determinant of the main matrix. Such a system of linear equations has a unique solution.

Let the following system of linear equations be given:

Where A-main matrix of the system:

the first of which needs to be found, and the second is given.

Since we assume that the determinant Δ of the matrix A is different from zero, then there is an inverse to A matrix A-1 . Then multiplying identity (2) from the left by the inverse matrix A-1 , we get:

inverse matrix has the following form:

Algorithm for solving a system of linear equations using the Cramer method

Calculate the determinant Δ of the main matrix A.
Replacing column 1 of a matrix A to the vector of free members b.
Calculation of the determinant Δ 1 of the resulting matrix A 1 .
Calculate Variable x 1 =Δ 1 /Δ.
Repeat steps 2−4 for columns 2, 3, ..., n matrices A.

Examples of solving SLEs using Cramer's method

Example 1. Solve the following system of linear equations using the Cramer method:

Let's replace column 1 of the matrix A per vector column b:

Replace column 2 of the matrix A per vector column b:

Replace column 3 of the matrix A per vector column b:

The solution to a system of linear equations is calculated as follows:

Let's write it in matrix form: Ax=b, Where

We select the largest modulo leading element of column 2. To do this, we swap rows 2 and 4. In this case, the sign of the determinant changes to “−”.

We select the leading element of column 3, largest in modulus. To do this, we swap rows 3 and 4. In this case, the sign of the determinant changes to “+”.

We have reduced the matrix to upper triangular form. The determinant of the matrix is equal to the product of all elements of the main diagonal:

To calculate the determinant of a matrix A 1, we reduce the matrix to upper triangular form, similar to the above procedure. We get the following matrix:

Replace column 2 of the matrix A per vector column b, we reduce the matrix to upper triangular form and calculate the determinant of the matrix:

,,,.

Consider a system of 3 equations with three unknowns

Using 3rd order determinants, the solution to such a system can be written in the same form as for a system of two equations, i.e.

(2.4)

if 0. Here

It's there Cramer's rule solving a system of three linear equations in three unknowns.

Example 2.3. Solve a system of linear equations using Cramer's rule:

Solution . Finding the determinant of the main matrix of the system

Since 0, then to find a solution to the system we can apply Cramer’s rule, but first we calculate three more determinants:

Examination:

Therefore, the solution was found correctly. 

Cramer's rules obtained for linear systems of 2nd and 3rd order suggest that the same rules can be formulated for linear systems of any order. Really happens

Cramer's theorem. Quadratic system of linear equations with a nonzero determinant of the main matrix of the system (0) has one and only one solution and this solution is calculated using the formulas

(2.5)

Where  – determinant of the main matrix,  i – matrix determinant, obtained from the main one, replacingith column column of free members.

Note that if =0, then Cramer’s rule does not apply. This means that the system either has no solutions at all or has infinitely many solutions.

Having formulated Cramer's theorem, the question naturally arises of calculating determinants of higher orders.

2.4. Determinants of nth order

Additional minor M ij element a ij is a determinant obtained from a given by deleting i th line and j th column. Algebraic complement A ij element a ij the minor of this element taken with the sign (–1) is called i + j, i.e. A ij = (–1) i + j M ij .

For example, let's find the minors and algebraic complements of the elements a 23 and a 31 qualifiers

We get



Using the concept of algebraic complement we can formulate determinant expansion theoremn-th order by row or column.

Theorem 2.1. Matrix determinantAis equal to the sum of the products of all elements of a certain row (or column) by their algebraic complements:

(2.6)

This theorem underlies one of the main methods for calculating determinants, the so-called. order reduction method. As a result of the expansion of the determinant n th order over any row or column, we get n determinants ( n–1)th order. To have fewer such determinants, it is advisable to select the row or column that has the most zeros. In practice, the expansion formula for the determinant is usually written as:

those. algebraic additions are written explicitly in terms of minors.

Examples 2.4. Calculate the determinants by first sorting them into some row or column. Typically, in such cases, select the column or row that has the most zeros. The selected row or column will be indicated by an arrow.



2.5. Basic properties of determinants

Expanding the determinant over any row or column, we get n determinants ( n–1)th order. Then each of these determinants ( n–1)th order can also be expanded into a sum of determinants ( n–2)th order. Continuing this process, one can reach the 1st order determinants, i.e. to the elements of the matrix whose determinant is calculated. So, to calculate 2nd order determinants, you will have to calculate the sum of two terms, for 3rd order determinants - the sum of 6 terms, for 4th order determinants - 24 terms. The number of terms will increase sharply as the order of the determinant increases. This means that calculating determinants of very high orders becomes a rather labor-intensive task, beyond the capabilities of even a computer. However, determinants can be calculated in another way, using the properties of determinants.

Property 1 . The determinant will not change if the rows and columns in it are swapped, i.e. when transposing a matrix:

This property indicates the equality of the rows and columns of the determinant. In other words, any statement about the columns of a determinant is also true for its rows and vice versa.

Property 2 . The determinant changes sign when two rows (columns) are interchanged.

Consequence . If the determinant has two identical rows (columns), then it is equal to zero.

Property 3 . The common factor of all elements in any row (column) can be taken out of the determinant sign.

For example,

Consequence . If all elements of a certain row (column) of a determinant are equal to zero, then the determinant itself is equal to zero.

Property 4 . The determinant will not change if the elements of one row (column) are added to the elements of another row (column), multiplied by any number.

For example,

Property 5 . The determinant of the product of matrices is equal to the product of the determinants of matrices:

Cramer's method is based on the use of determinants in solving systems of linear equations. This significantly speeds up the solution process.

Cramer's method can be used to solve a system of as many linear equations as there are unknowns in each equation. If the determinant of the system is not equal to zero, then Cramer’s method can be used in the solution, but if it is equal to zero, then it cannot. In addition, Cramer's method can be used to solve systems of linear equations that have a unique solution.

Definition. A determinant made up of coefficients for unknowns is called a determinant of the system and is denoted (delta).

Determinants

are obtained by replacing the coefficients of the corresponding unknowns with free terms:

;

Cramer's theorem. If the determinant of the system is nonzero, then the system of linear equations has one unique solution, and the unknown is equal to the ratio of the determinants. The denominator contains the determinant of the system, and the numerator contains the determinant obtained from the determinant of the system by replacing the coefficients of this unknown with free terms. This theorem holds for a system of linear equations of any order.

Example 1. Solve a system of linear equations:

According to Cramer's theorem we have:

So, the solution to system (2):

online calculator, Cramer's solving method.

Three cases when solving systems of linear equations

As is clear from Cramer's theorem, when solving a system of linear equations, three cases can occur:

First case: a system of linear equations has a unique solution

(the system is consistent and definite)

Second case: a system of linear equations has an infinite number of solutions

(the system is consistent and uncertain)

** ,

those. the coefficients of the unknowns and the free terms are proportional.

Third case: the system of linear equations has no solutions

(the system is inconsistent)

So the system m linear equations with n called variables non-joint, if she does not have a single solution, and joint, if it has at least one solution. A simultaneous system of equations that has only one solution is called certain, and more than one – uncertain.

Examples of solving systems of linear equations using the Cramer method

Let the system be given

Based on Cramer's theorem

………….
,

Where
-

system determinant. We obtain the remaining determinants by replacing the column with the coefficients of the corresponding variable (unknown) with free terms:

Example 2.

Therefore, the system is definite. To find its solution, we calculate the determinants

Using Cramer's formulas we find:

So, (1; 0; -1) is the only solution to the system.

To check solutions to systems of equations 3 X 3 and 4 X 4, you can use an online calculator using Cramer's solving method.

If in a system of linear equations there are no variables in one or more equations, then in the determinant the corresponding elements are equal to zero! This is the next example.

Example 3. Solve a system of linear equations using the Cramer method:

Solution. We find the determinant of the system:

Look carefully at the system of equations and at the determinant of the system and repeat the answer to the question in which cases one or more elements of the determinant are equal to zero. So, the determinant is not equal to zero, therefore the system is definite. To find its solution, we calculate the determinants for the unknowns

Using Cramer's formulas we find:

So, the solution to the system is (2; -1; 1).

To check solutions to systems of equations 3 X 3 and 4 X 4, you can use an online calculator using Cramer's solving method.

Top of page

We continue to solve systems using Cramer's method together

As already mentioned, if the determinant of the system is equal to zero, and the determinants of the unknowns are not equal to zero, the system is inconsistent, that is, it has no solutions. Let us illustrate with the following example.

Example 6. Solve a system of linear equations using the Cramer method:

Solution. We find the determinant of the system:

The determinant of the system is equal to zero, therefore, the system of linear equations is either inconsistent and definite, or inconsistent, that is, has no solutions. To clarify, we calculate determinants for unknowns

The determinants of the unknowns are not equal to zero, therefore, the system is inconsistent, that is, it has no solutions.

To check solutions to systems of equations 3 X 3 and 4 X 4, you can use an online calculator using Cramer's solving method.

In problems involving systems of linear equations, there are also those where, in addition to letters denoting variables, there are also other letters. These letters represent a number, most often real. In practice, search problems lead to such equations and systems of equations general properties any phenomena or objects. That is, have you invented any new material or a device, and to describe its properties, which are common regardless of the size or number of an instance, you need to solve a system of linear equations, where instead of some coefficients for variables there are letters. You don't have to look far for examples.

The following example is for a similar problem, only the number of equations, variables, and letters denoting a certain real number increases.

Example 8. Solve a system of linear equations using the Cramer method: