Line 10: Line 10:
  
 
Let
 
Let
:<math>\mathbf{v} = \begin{pmatrix}
+
:<math>\mathbf{v} = \begin{bmatrix}
 
a \\
 
a \\
b \end{pmatrix}</math>  
+
b \end{bmatrix}</math>  
  
 
which denotes a vector between a point and the origin.
 
which denotes a vector between a point and the origin.
Line 22: Line 22:
  
 
Let
 
Let
:<math>\mathbf{w} = \begin{pmatrix}
+
:<math>\mathbf{w} = \begin{bmatrix}
 
c \\
 
c \\
d \end{pmatrix}</math>.
+
d \end{bmatrix}</math>.
 
We have,
 
We have,
:<math>\mathbf{v-w} = \begin{pmatrix}
+
:<math>\mathbf{v-w} = \begin{bmatrix}
 
a-c \\
 
a-c \\
b-d \end{pmatrix}</math>,
+
b-d \end{bmatrix}</math>,
 
and
 
and
 
:<math>\mathbf{\|v-w\|} = \sqrt{(a-c)^2 +(b-d)^2}</math>.
 
:<math>\mathbf{\|v-w\|} = \sqrt{(a-c)^2 +(b-d)^2}</math>.
  
 
In short, there is no significant difference in the three dimensional approach of the form
 
In short, there is no significant difference in the three dimensional approach of the form
:<math>\mathbf{v} = \begin{pmatrix}
+
:<math>\mathbf{v} = \begin{bmatrix}
 
a \\
 
a \\
 
b \\
 
b \\
c \end{pmatrix}</math>.
+
c \end{bmatrix}</math>.
  
 
Another essential concept is the angle between two vectors as shown in the following formula:
 
Another essential concept is the angle between two vectors as shown in the following formula:

Revision as of 16:49, 25 November 2010

Inner Product Spaces and Orthogonal Complements

Introduction

The following entries are derived from a relatively large yet concise topic called Inner Product Spaces. I would only focus on two subtopics which are the Inner Product Spaces themselves and Orthogonal Complements. Other essential subtopics would also be posted in the form of background knowledge to ensure the thoroughness of readers' understanding. Please also note that the Cross Products subtopic is not required in the context of MA 26500.

Part 1: Inner Product Spaces

Background Knowledge - The Basics of Vectors

Let

$ \mathbf{v} = \begin{bmatrix} a \\ b \end{bmatrix} $

which denotes a vector between a point and the origin.

Then the length of this vector is given by

$ \mathbf{\|v\|} = \sqrt{x^2 +y^2} $.

The same concept applies for two-point case between points v and w as shown below.

Let

$ \mathbf{w} = \begin{bmatrix} c \\ d \end{bmatrix} $.

We have,

$ \mathbf{v-w} = \begin{bmatrix} a-c \\ b-d \end{bmatrix} $,

and

$ \mathbf{\|v-w\|} = \sqrt{(a-c)^2 +(b-d)^2} $.

In short, there is no significant difference in the three dimensional approach of the form

$ \mathbf{v} = \begin{bmatrix} a \\ b \\ c \end{bmatrix} $.

Another essential concept is the angle between two vectors as shown in the following formula:

$ \cos{\alpha} = \frac{\langle\mathbf{v}\, , \mathbf{w}\rangle}{\|\mathbf{v}\| \, \|\mathbf{w}\|} $.

This will be more prominent as we go through Inner Product Spaces section.

Lastly, a unit vector is a vector that has magnitude one and denoted as in the following:

$ \boldsymbol{\hat{w}} = \frac{\boldsymbol{w}}{\|\boldsymbol{w}\|} $.

Inner Product Spaces

Part 2: Orthogonal Complements

Background Knowledge - Gram-Schmidt Algorithm

Orthogonal Complements

Part 3: Applications

Generic Homework Problems

Generic Exam Problems


Ryan Jason Tedjasukmana

Alumni Liaison

Prof. Math. Ohio State and Associate Dean
Outstanding Alumnus Purdue Math 2008

Jeff McNeal