Difference between revisions of "Inner Products MA265F10Walther" - Rhea

Revision as of 15:27, 6 December 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 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

Inner Product Spaces

Part 2: Orthogonal Complements

Background Knowledge - Gram-Schmidt Algorithm

Orthogonal Complements

Ryan Jason Tedjasukmana

Back to MA265 Fall 2010 Prof Walther

Back to MA265

@@ Line 1: / Line 1: @@
 == '''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 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 [[MA265|MA 26500]].
-----
 '''Part 1: Inner Product Spaces'''
+----
 ''[[Background Knowledge - The Basics of Vectors]]''
-Let
-:<math>\mathbf{v} = \begin{bmatrix}
-a \\
-b \end{bmatrix}</math>
-which denotes a vector between a point and the origin.
+''Inner Product Spaces''
-Then the length of this vector is given by
-:<math>\mathbf{\|v\|} = \sqrt{x^2 +y^2}</math>.
-The same concept applies for two-point case between points '''v''' and '''w''' as shown below.
+'''Part 2: Orthogonal Complements'''
-Let
-:<math>\mathbf{w} = \begin{bmatrix}
-c \\
-d \end{bmatrix}</math>.
-We have,
-:<math>\mathbf{v-w} = \begin{bmatrix}
-a-c \\
-b-d \end{bmatrix}</math>,
-and
-:<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
-:<math>\mathbf{v} = \begin{bmatrix}
-p \\
-q \\
-r \end{bmatrix}</math>.
-Another essential concept is the angle between two vectors as shown in the following formula:
-:<math> \cos{\alpha} = \frac{\langle\mathbf{v}\, , \mathbf{w}\rangle}{\|\mathbf{v}\| \, \|\mathbf{w}\|}</math>.
-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:
-:<math alt=>\boldsymbol{\hat{w}} = \frac{\boldsymbol{w}}{\|\boldsymbol{w}\|}</math>.
-''Inner Product Spaces''
 ----
+''[[Background Knowledge - Gram-Schmidt Algorithm]]''
-'''Part 2: Orthogonal Complements'''
-''Background Knowledge - Gram-Schmidt Algorithm''
-In the simplest review, the Gram-Schmidt Algorithm is shown in the following pattern for vectors '''u''' and '''v'''.
-: <math>
-\begin{align}
-\mathbf{u}_1 & = \mathbf{v}_1, \\
-\mathbf{u}_2 & = \mathbf{v}_2-\mathrm{proj}_{\mathbf{u}_1}\,(\mathbf{v}_2),
-\\
-\mathbf{u}_3 & = \mathbf{v}_3-\mathrm{proj}_{\mathbf{u}_1}\,(\mathbf{v}_3)-\mathrm{proj}_{\mathbf{u}_2}\,(\mathbf{v}_3), \\
-& {}\ \  \vdots \\
-\mathbf{u}_k & = \mathbf{v}_k-\sum_{j=1}^{k-1}\mathrm{proj}_{\mathbf{u}_j}\,(\mathbf{v}_k),
-\end{align}
-</math>
-where
-:<math>\mathrm{proj}_{\mathbf{u}}\,(\mathbf{v}) = {\langle \mathbf{v}, \mathbf{u}\rangle\over\langle \mathbf{u}, \mathbf{u}\rangle}\mathbf{u} </math>.
 ''Orthogonal Complements''

Difference between revisions of "Inner Products MA265F10Walther" - Rhea

Revision as of 15:27, 6 December 2010

Inner Product Spaces and Orthogonal Complements

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