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  Inner product spaces, Orthogonal and Orthonormal Vectors 
 
 
Institute of Lifelong Learning, University of Delhi                                        
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lesson: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 
Lesson Developer : Umesh Chand 
 
Department / College: Department of Mathematics, Kirorimal 
College, University of Delhi 
 
 
 
 
 
 
 
 
 
  
Page 2


  Inner product spaces, Orthogonal and Orthonormal Vectors 
 
 
Institute of Lifelong Learning, University of Delhi                                        
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lesson: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 
Lesson Developer : Umesh Chand 
 
Department / College: Department of Mathematics, Kirorimal 
College, University of Delhi 
 
 
 
 
 
 
 
 
 
  
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 2 
 
Table of Contents: 
Chapter: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 1. Learning outcomes 
 2. Introduction 
 3. Inner product space 
 4. Norm 
 5. Orthogonaility 
 6. Orthogonal complement 
 ? Summary 
 ? Exercise 
 ? References/Bibliography/Further reading  
 
 
 
 
 
 
 
 
 
 
 
 
Page 3


  Inner product spaces, Orthogonal and Orthonormal Vectors 
 
 
Institute of Lifelong Learning, University of Delhi                                        
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lesson: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 
Lesson Developer : Umesh Chand 
 
Department / College: Department of Mathematics, Kirorimal 
College, University of Delhi 
 
 
 
 
 
 
 
 
 
  
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 2 
 
Table of Contents: 
Chapter: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 1. Learning outcomes 
 2. Introduction 
 3. Inner product space 
 4. Norm 
 5. Orthogonaility 
 6. Orthogonal complement 
 ? Summary 
 ? Exercise 
 ? References/Bibliography/Further reading  
 
 
 
 
 
 
 
 
 
 
 
 
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 3 
 
 
1. Learning outcomes 
After studying the whole content student will be able to understand 
 ? Inner product space 
 ? Norm 
 ? Orthogonaility 
 ? Orthogonal complement 
 ? Schwarz inequality 
 ? Bessel inequality 
 
 
 
2. Introduction 
In linear algebra, an inner product space is vector space with 
additional structure called inner product. This additional structure 
associates each pair of vectors in the space with a scalar quantity 
know as the inner product of vectors. Inner products allow the 
rigorous introduction of intuitive geometrical notions such as the 
length of a vector or angle between two vectors. Inner product 
space generalize Euclidean space (in which the inner product is the 
det product, also known as scalar product) to vector spaces of any 
(possibility infinite) functional analysis. 
 
 
 
Page 4


  Inner product spaces, Orthogonal and Orthonormal Vectors 
 
 
Institute of Lifelong Learning, University of Delhi                                        
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lesson: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 
Lesson Developer : Umesh Chand 
 
Department / College: Department of Mathematics, Kirorimal 
College, University of Delhi 
 
 
 
 
 
 
 
 
 
  
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 2 
 
Table of Contents: 
Chapter: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 1. Learning outcomes 
 2. Introduction 
 3. Inner product space 
 4. Norm 
 5. Orthogonaility 
 6. Orthogonal complement 
 ? Summary 
 ? Exercise 
 ? References/Bibliography/Further reading  
 
 
 
 
 
 
 
 
 
 
 
 
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 3 
 
 
1. Learning outcomes 
After studying the whole content student will be able to understand 
 ? Inner product space 
 ? Norm 
 ? Orthogonaility 
 ? Orthogonal complement 
 ? Schwarz inequality 
 ? Bessel inequality 
 
 
 
2. Introduction 
In linear algebra, an inner product space is vector space with 
additional structure called inner product. This additional structure 
associates each pair of vectors in the space with a scalar quantity 
know as the inner product of vectors. Inner products allow the 
rigorous introduction of intuitive geometrical notions such as the 
length of a vector or angle between two vectors. Inner product 
space generalize Euclidean space (in which the inner product is the 
det product, also known as scalar product) to vector spaces of any 
(possibility infinite) functional analysis. 
 
 
 
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 4 
 
 
 
3.  Inner Product Space 
Let V be a vector space over F. An inner product on V is a function 
V ?V to f that assign every ordered pair of vectors x, y in V, to a 
scalar in F, denoted by x, y , in such a way that 
(i) x y,z x,z y,z x,y,z V ? ? ? ? ?  
(ii) cx,y c x,y c F ? ? ?  and x, y ? V 
(iii) x,y y,x x,y V ? ? ? 
(iv) x,x 0 if x 0 ?? 
Then the vector space V is said to be inner product space with 
respect to the specified inner product defined on it. 
Value Addition : Note 
1. (i) and (ii) are equivalent to  
x y, z x,z y,z , F, x,y,z V ? ? ? ? ? ? ? ? ? ? ? ? 
2. (i) and (ii) imply inner product is linear in Ist component, 
property (1) and (ii) Jointly is called linearly property, (iii) is 
called conjugate symmetry, (iv) is called non-negative. 
 
Example 1: Let V = F
n
, F = R (or C) 
Let  x = (a
1
, a
2
, …, a
n
), 
          ? V  
y ? (b
1
, b
2
, …,b
n
). 
Page 5


  Inner product spaces, Orthogonal and Orthonormal Vectors 
 
 
Institute of Lifelong Learning, University of Delhi                                        
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
Lesson: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 
Lesson Developer : Umesh Chand 
 
Department / College: Department of Mathematics, Kirorimal 
College, University of Delhi 
 
 
 
 
 
 
 
 
 
  
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 2 
 
Table of Contents: 
Chapter: Inner product spaces, Orthogonal and Orthonormal 
Vectors 
 1. Learning outcomes 
 2. Introduction 
 3. Inner product space 
 4. Norm 
 5. Orthogonaility 
 6. Orthogonal complement 
 ? Summary 
 ? Exercise 
 ? References/Bibliography/Further reading  
 
 
 
 
 
 
 
 
 
 
 
 
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 3 
 
 
1. Learning outcomes 
After studying the whole content student will be able to understand 
 ? Inner product space 
 ? Norm 
 ? Orthogonaility 
 ? Orthogonal complement 
 ? Schwarz inequality 
 ? Bessel inequality 
 
 
 
2. Introduction 
In linear algebra, an inner product space is vector space with 
additional structure called inner product. This additional structure 
associates each pair of vectors in the space with a scalar quantity 
know as the inner product of vectors. Inner products allow the 
rigorous introduction of intuitive geometrical notions such as the 
length of a vector or angle between two vectors. Inner product 
space generalize Euclidean space (in which the inner product is the 
det product, also known as scalar product) to vector spaces of any 
(possibility infinite) functional analysis. 
 
 
 
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 4 
 
 
 
3.  Inner Product Space 
Let V be a vector space over F. An inner product on V is a function 
V ?V to f that assign every ordered pair of vectors x, y in V, to a 
scalar in F, denoted by x, y , in such a way that 
(i) x y,z x,z y,z x,y,z V ? ? ? ? ?  
(ii) cx,y c x,y c F ? ? ?  and x, y ? V 
(iii) x,y y,x x,y V ? ? ? 
(iv) x,x 0 if x 0 ?? 
Then the vector space V is said to be inner product space with 
respect to the specified inner product defined on it. 
Value Addition : Note 
1. (i) and (ii) are equivalent to  
x y, z x,z y,z , F, x,y,z V ? ? ? ? ? ? ? ? ? ? ? ? 
2. (i) and (ii) imply inner product is linear in Ist component, 
property (1) and (ii) Jointly is called linearly property, (iii) is 
called conjugate symmetry, (iv) is called non-negative. 
 
Example 1: Let V = F
n
, F = R (or C) 
Let  x = (a
1
, a
2
, …, a
n
), 
          ? V  
y ? (b
1
, b
2
, …,b
n
). 
Inner product spaces, Orthogonal and Orthonormal Vectors 
Institute of Lifelong Learning, University of Delhi                                       pg. 5 
 
Define 
n
1 1 2 2 n n i i
i1
x, y a b a b .... a b a b
?
? ? ? ? ?
?
 
Then it is an inner product  on V, called standard inner product. 
Verification: Let x, y, z ? V, where  
 x = (a
1
, a
2
, …, a
n
), y = (b
1
, b
2
, ….,.b
n
), z = (c, c
2
, …, c
n
) 
(i) 
n
i i i
i1
x y,z (a b )c
?
? ? ?
?
 
nn
i i i i
i 1 i 1
a c b c
??
??
??
 
x,z y,z ?? 
(ii) 
n
ii
i1
cx, y ca b
?
?
?
 
n
ii
i1
c a b
?
?
?
 
c x, y ? 
(iii) 
n
ii
i1
x, y a b
?
?
?
 
n
ii
i1
ab
?
?
?
 
n
ii
i1
ba
?
?
?
 
y,x ? 
(iv) 
n
ii
i1
x,x a a 0
?
??
?
  if x ? 0 
Thus x, y is an inner product on V. 
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FAQs on Lecture 4 - Inner Product spaces, Orthogonal and Orthonormal Vectors - Linear Algebra - Engineering Mathematics

1. What is an inner product space?
An inner product space is a vector space equipped with an inner product, which is a function that takes two vectors as inputs and returns a scalar. The inner product satisfies certain properties such as linearity, conjugate symmetry, and positive definiteness. It allows us to define concepts such as length (norm) and angle between vectors in the vector space.
2. How are orthogonal vectors defined in an inner product space?
In an inner product space, two vectors are said to be orthogonal if their inner product is zero. Geometrically, this means that the angle between the vectors is 90 degrees. Orthogonal vectors are important in various applications, such as finding a basis for a subspace or solving systems of linear equations.
3. What is the significance of orthonormal vectors in engineering mathematics?
Orthonormal vectors are a special case of orthogonal vectors where each vector has a norm of 1. They form an orthonormal basis for the vector space, which means that they are linearly independent and span the entire space. Orthonormal vectors have several advantages in engineering mathematics, such as simplifying calculations involving inner products and providing an intuitive geometric interpretation.
4. How can we determine if a set of vectors is orthonormal?
To determine if a set of vectors is orthonormal, we need to check two conditions: orthogonality and norm. First, we compute the inner product between every pair of vectors in the set. If all the inner products are zero (orthogonal), then the vectors are orthogonal. Second, we calculate the norm of each vector and check if it equals 1. If both conditions are satisfied, the set of vectors is orthonormal.
5. Can any vector space be an inner product space?
No, not every vector space can be an inner product space. In order for a vector space to be an inner product space, it must satisfy certain properties. These properties include the linearity of the inner product, conjugate symmetry, and positive definiteness. If a vector space does not have these properties, it cannot be equipped with an inner product and therefore cannot be an inner product space.
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