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10.1 Gaussian Elimination Method

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1 10.1 Gaussian Elimination Method
Linear Algebra 10.1 Gaussian Elimination Method Quiz # 3, Monday 20 on sections: 9.3, 10.1

2 Objective Introduction to Matrices Elementary Row Operations
Gaussian Elimination Method

3 Matrices Definition An equation such as x+3y=9 is called a linear equation. The graph of this equation is a straight line in the x-y plane. A pair of values of x and y that satisfy the equation is called a solution.

4 Definition A linear equation in n variables x1, x2, x3, …, xn has the form a1 x1 + a2 x2 + a3 x3 + … + an xn = b where the coefficients a1, a2, a3, …, an and b are real numbers.

5 Solutions for System of Linear Equations
Figure 1.2 No solution –2x + y = 3 –4x + 2y = 2 Lines are parallel. No point of intersection. No solutions. Figure 1.3 Many solution) 4x – 2y = 6 6x – 3y = 9 Both equations have the same graph. Any point on the graph is a solution. Many solutions. Figure 1.1 Unique solution x + 3y = 9 –2x + y = –4 Lines intersect at (3, 2) Unique solution: x = 3, y = 2.

6 A linear equation in three variables corresponds to a plane in three-dimensional space.
※ Systems of three linear equations in three variables: Unique solution( one solution)

7 No solutions Many solutions

8 How to solve a system of linear equations?
Gaussian Elimination Method. Gaussian –Jordan Method Grammars Rule ….etc

9 Definition A matrix is a rectangular array of numbers.
The numbers in the array are called the elements of the matrix. Examples of Matrices

10 General Form of A Matrix:
(i, j)-th entry: Number of rows: m Number of columns: n size: m×n

11 Row and Column

12 Size and Type Location Identity Matrices aijrow i, column j
diagonal 1,0,I size

13 Diagonal matrix: Square matrix: m = n

14 Example 1

15 Row Echelon Form Definition A matrix is in row echelon form if
Any rows consisting entirely of zeros are grouped at the bottom of the matrix. The first nonzero element of each other row is 1. This element is called a leading 1. The leading 1 of each row after the first is positioned to the right of the leading 1 of the previous row.

16 Examples for reduced echelon form
() () () () elementary row operations are used to put a matrix in the row echelon form.

17 Elementary Row Operations of Matrices
Elementary Transformation Interchange two equations. 2. Multiply both sides of an equation by a nonzero constant. 3. Add a multiple of one equation to another equation. Elementary Row Operation Interchange two rows of a matrix. Multiply the elements of a row by a nonzero constant. Add a multiple of the elements of one row to the corresponding elements of another row.

18 Example 2 Use the elementary row operations to find the row echelon form of the following matrix. Solution pivot leading 1) pivot pivot The matrix is the row echelon form of the given matrix.

19 Solving Linear Systems by Gaussian Elimination Method
System of linear equations  form augmented matrix  put the augmented matrix in row echelon from  solve by back substitution

20 Matrix form of a system of linear equations:
= A x b

21 matrix of coefficient and augmented matrix

22 Example 3 Solving the following system of linear equation. Solution
row equivalent Solution Equation Method Initial system: Analogous Matrix Method Augmented matrix: Eq2+(–2)Eq1 Eq3+(–1)Eq1 R2+(–2)R1 R3+(–1)R1

23 Eq3+(2)Eq2 R3+(2)R2 (–1/5)Eq3 Back substitution (–1/5)R3 The solution is The solution is

24 Example 4 Solving the following system of linear equation. Solution

25 Example 5 Solve the system Solution

26 Example 6 Solve, if possible, the system of equations Solution
The general solution to the system is

27 Example 7 Solve the system of equations  many sol. Solution

28 Example 8 Solve the system of equations Solution

29 Example 9 This example illustrates a system that has no solution. Let us try to solve the system Solution 0x1+0x2+0x3=1 The system has no solution.

30 Homogeneous System of linear Equations
Note. trivial solution The system has other nontrivial solutions. Example: Theorem A system of homogeneous linear equations that has more variables than equations has many solutions.

31 Summary If , then the system is independent If
, then the system is dependent If , then the system is inconsistent

32 Exercises Ex 55: Find all values of a for which the following system has a unique solution

33 Ex :Find the interpolating polynomial that passes through the points ( -3,28), (-1,6)
and (2,3)

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