Page 1
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 1
Paper: Linear Algebra
Lesson: System of Linear Equations and Matrices
Course Developer: Parvinder Kaur
Department/College: Assistant Professor, Department of
Mathematics, Motilal Nehru College, University of Delhi
Page 2
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 1
Paper: Linear Algebra
Lesson: System of Linear Equations and Matrices
Course Developer: Parvinder Kaur
Department/College: Assistant Professor, Department of
Mathematics, Motilal Nehru College, University of Delhi
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 2
Table of Contents:
Chapter : System of Linear Equations and Matrices
1. Learning outcomes
2. Systems of Linear Equations and Matrices
2.1 Introduction
2.2 Linear equations
2.3 System of Linear equations
3. Matrices and Elementary operations
3.1 Matrix representation of a linear system of equations
3.2 Elementary operations
3.3 Elementary matrices
3.4 Equivalent systems
3.5 Row equivalence
4. Special Matrices and their applications
4.1 Triangular Matrix
4.2 Reduced Row echelon matrix
4.3 Solving system of linear equations using Gaussian Elimination
Method
4.4 Solving system of linear equations using Gauss Jordan Elimination
Method
5. Rank
5.1 Rank of a matrix
5.2 Linearly Dependent and Linearly Independent Vectors
5.3 Row Rank and Column Rank
5.4 Consistency of system of linear equations
Exercise
Summary
References
Page 3
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 1
Paper: Linear Algebra
Lesson: System of Linear Equations and Matrices
Course Developer: Parvinder Kaur
Department/College: Assistant Professor, Department of
Mathematics, Motilal Nehru College, University of Delhi
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 2
Table of Contents:
Chapter : System of Linear Equations and Matrices
1. Learning outcomes
2. Systems of Linear Equations and Matrices
2.1 Introduction
2.2 Linear equations
2.3 System of Linear equations
3. Matrices and Elementary operations
3.1 Matrix representation of a linear system of equations
3.2 Elementary operations
3.3 Elementary matrices
3.4 Equivalent systems
3.5 Row equivalence
4. Special Matrices and their applications
4.1 Triangular Matrix
4.2 Reduced Row echelon matrix
4.3 Solving system of linear equations using Gaussian Elimination
Method
4.4 Solving system of linear equations using Gauss Jordan Elimination
Method
5. Rank
5.1 Rank of a matrix
5.2 Linearly Dependent and Linearly Independent Vectors
5.3 Row Rank and Column Rank
5.4 Consistency of system of linear equations
Exercise
Summary
References
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 3
1. Learning Outcomes
After Reading this chapter students will be able to understand:
? Homogeneous system of linear equations
? Non-Homogeneous system of linear equations
? The transformations which produces equivalent systems
? Triangular Matrix
? Row reduced echelon Matrix
? Gaussian Elimination method to transform a system of linear equations
into an equivalent system in row echelon form
? Gauss Jordan elimination method to transform a system of linear
equations into an equivalent system in Reduced row echelon form
? Rank, Row Rank and Column Rank of a matrix
? Solving systems of linear equations using Rank of a matrix
? Consistency of the system of linear equations.
Page 4
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 1
Paper: Linear Algebra
Lesson: System of Linear Equations and Matrices
Course Developer: Parvinder Kaur
Department/College: Assistant Professor, Department of
Mathematics, Motilal Nehru College, University of Delhi
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 2
Table of Contents:
Chapter : System of Linear Equations and Matrices
1. Learning outcomes
2. Systems of Linear Equations and Matrices
2.1 Introduction
2.2 Linear equations
2.3 System of Linear equations
3. Matrices and Elementary operations
3.1 Matrix representation of a linear system of equations
3.2 Elementary operations
3.3 Elementary matrices
3.4 Equivalent systems
3.5 Row equivalence
4. Special Matrices and their applications
4.1 Triangular Matrix
4.2 Reduced Row echelon matrix
4.3 Solving system of linear equations using Gaussian Elimination
Method
4.4 Solving system of linear equations using Gauss Jordan Elimination
Method
5. Rank
5.1 Rank of a matrix
5.2 Linearly Dependent and Linearly Independent Vectors
5.3 Row Rank and Column Rank
5.4 Consistency of system of linear equations
Exercise
Summary
References
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 3
1. Learning Outcomes
After Reading this chapter students will be able to understand:
? Homogeneous system of linear equations
? Non-Homogeneous system of linear equations
? The transformations which produces equivalent systems
? Triangular Matrix
? Row reduced echelon Matrix
? Gaussian Elimination method to transform a system of linear equations
into an equivalent system in row echelon form
? Gauss Jordan elimination method to transform a system of linear
equations into an equivalent system in Reduced row echelon form
? Rank, Row Rank and Column Rank of a matrix
? Solving systems of linear equations using Rank of a matrix
? Consistency of the system of linear equations.
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 4
2. System of Linear Equations and Matrices:
2.1 Introduction:
Linear Algebra is one of the most interesting and applicable areas of
mathematics. It has wide application in all the areas of mathematics. The theory of
linear equations plays a significant and motivating role in the subject of linear algebra. In
fact, many problems in linear algebra are equivalent to studying a system of linear
equations. The aim of this chapter is to learn about the linear systems and their
solutions. We will study the notion of a matrix so that we can approach any system via
its coefficient matrix. This makes us to mention a set of rules called elementary
operations to transform the system of equations into a reduced row echelon form of the
system.
2.2 Linear Equations:
The linear equation is an expression of the form
1 1 2 2
...
nn
ax a x a x b ? ? ? ? (1)
where , ?
i
a b R and '
i
xs are unknowns (or variables). The scalars a
i
are called the
coefficient of the '
i
xs respectively and b is called the constant term.
A set of values for the unknowns, say
1 1 2 2
, , ... ,
nn
x x x ? ? ? ? ? ? is said to be solution
of (1) if the statement obtained by substituting
i
? for
i
x
1 1 2 2
...
nn
a a a b ? ? ? ? ? ? ? is true.
This set of values is then said to satisfy the equation we denote this solution by simply
the n-tuple ? ?
12
, ,..., . ? ? ? ?
n
U
Value Addition:
A linear equation can have infinitely many solutions, exactly one solution (Unique
Solution) or no solution at all.
2.3 System of linear equations
A system of linear equations is a finite collection of linear equations in some
unknowns. For instance, a linear system of m equation in n variables
12
, ,...,
n
x x x can be
written as
Page 5
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 1
Paper: Linear Algebra
Lesson: System of Linear Equations and Matrices
Course Developer: Parvinder Kaur
Department/College: Assistant Professor, Department of
Mathematics, Motilal Nehru College, University of Delhi
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 2
Table of Contents:
Chapter : System of Linear Equations and Matrices
1. Learning outcomes
2. Systems of Linear Equations and Matrices
2.1 Introduction
2.2 Linear equations
2.3 System of Linear equations
3. Matrices and Elementary operations
3.1 Matrix representation of a linear system of equations
3.2 Elementary operations
3.3 Elementary matrices
3.4 Equivalent systems
3.5 Row equivalence
4. Special Matrices and their applications
4.1 Triangular Matrix
4.2 Reduced Row echelon matrix
4.3 Solving system of linear equations using Gaussian Elimination
Method
4.4 Solving system of linear equations using Gauss Jordan Elimination
Method
5. Rank
5.1 Rank of a matrix
5.2 Linearly Dependent and Linearly Independent Vectors
5.3 Row Rank and Column Rank
5.4 Consistency of system of linear equations
Exercise
Summary
References
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 3
1. Learning Outcomes
After Reading this chapter students will be able to understand:
? Homogeneous system of linear equations
? Non-Homogeneous system of linear equations
? The transformations which produces equivalent systems
? Triangular Matrix
? Row reduced echelon Matrix
? Gaussian Elimination method to transform a system of linear equations
into an equivalent system in row echelon form
? Gauss Jordan elimination method to transform a system of linear
equations into an equivalent system in Reduced row echelon form
? Rank, Row Rank and Column Rank of a matrix
? Solving systems of linear equations using Rank of a matrix
? Consistency of the system of linear equations.
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 4
2. System of Linear Equations and Matrices:
2.1 Introduction:
Linear Algebra is one of the most interesting and applicable areas of
mathematics. It has wide application in all the areas of mathematics. The theory of
linear equations plays a significant and motivating role in the subject of linear algebra. In
fact, many problems in linear algebra are equivalent to studying a system of linear
equations. The aim of this chapter is to learn about the linear systems and their
solutions. We will study the notion of a matrix so that we can approach any system via
its coefficient matrix. This makes us to mention a set of rules called elementary
operations to transform the system of equations into a reduced row echelon form of the
system.
2.2 Linear Equations:
The linear equation is an expression of the form
1 1 2 2
...
nn
ax a x a x b ? ? ? ? (1)
where , ?
i
a b R and '
i
xs are unknowns (or variables). The scalars a
i
are called the
coefficient of the '
i
xs respectively and b is called the constant term.
A set of values for the unknowns, say
1 1 2 2
, , ... ,
nn
x x x ? ? ? ? ? ? is said to be solution
of (1) if the statement obtained by substituting
i
? for
i
x
1 1 2 2
...
nn
a a a b ? ? ? ? ? ? ? is true.
This set of values is then said to satisfy the equation we denote this solution by simply
the n-tuple ? ?
12
, ,..., . ? ? ? ?
n
U
Value Addition:
A linear equation can have infinitely many solutions, exactly one solution (Unique
Solution) or no solution at all.
2.3 System of linear equations
A system of linear equations is a finite collection of linear equations in some
unknowns. For instance, a linear system of m equation in n variables
12
, ,...,
n
x x x can be
written as
System of Linear Equations and Matrices
Institute of Lifelong Learning, University of Delhi pg. 5
11 1 12 2 1 1
...
nn
a x a x a x b ? ? ? ? (2)
21 1 22 2 2 2
...
nn
a x a x a x b ? ? ? ?
? ?
1 1 2 2
...
m m mn n m
a x a x a x b ? ? ? ?
A solution of linear system (2) is a tuple ? ?
12
, ,...,
n
? ? ? of numbers that makes each
equation a true statement when the values
12
, ,...,
n
? ? ? are substituted for
12
, ,...,
n
x x x
respectively. The set of all solution of a linear system is called the solution set or general
solution of the system.
System of Linear Equations
Consistent Inconsistent
Unique solution Infinitely many No Solution
solutions
A system of equations is called consistent if there exists a solution otherwise it is called
as inconsistent.
The system of linear equations
11 1 12 2 1
... 0
nn
a x a x a x ? ? ? ? (3)
21 1 22 2 2
... 0
nn
a x a x a x ? ? ? ?
? ?
1 1 2 2
... 0
m m mn n
a x a x a x ? ? ? ?
where all b
i
's are zero is called the Homogeneous system of equations. Whereas the
system of equations (2) is termed as non-Homogeneous system of equation. The
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