Line 7: Line 7:
 
2. '''Associative Property''':  
 
2. '''Associative Property''':  
  
'''·'''a. Of addition: (u + v) + w = u = (v + w)
+
'''·''' Of addition: (u + v) + w = u = (v + w)
  
'''·'''b. Of multiplication: (ab)v = a(bv)
+
'''·''' Of multiplication: (ab)v = a(bv)
  
3. '''Zero Property''': There exist some '''0'''x∈V such that '''0''' + v = v
+
3. '''Zero Property''': There exist some '''0'''∈V such that '''0''' + v = v
  
 
4. '''Inverse Property''': For every v∈V there is some w∈V such that v+w=0
 
4. '''Inverse Property''': For every v∈V there is some w∈V such that v+w=0
Line 18: Line 18:
  
 
6. '''Distributive Property''': a(u + v) = au + av
 
6. '''Distributive Property''': a(u + v) = au + av
 +
 +
 +
'''Example'''
 +
  
  
Line 24: Line 28:
 
===SUBSPACE===
 
===SUBSPACE===
  
To be a '''subspace''' of vectors the following must be true:
+
A '''subspace''' is a subset of a vector space. To be a subspace of vectors the following must be true:
  
 
1. One set must be a '''subset''' of another set
 
1. One set must be a '''subset''' of another set

Revision as of 11:26, 3 December 2012

VECTOR SPACE

A vector space is a set of vectors that defines addition V x V --> V and scalar multiplcation cV --> V that satisfy the following properties:

1. Communative Property: u + v = v + u

2. Associative Property:

· Of addition: (u + v) + w = u = (v + w)

· Of multiplication: (ab)v = a(bv)

3. Zero Property: There exist some 0∈V such that 0 + v = v

4. Inverse Property: For every v∈V there is some w∈V such that v+w=0

5. Identity Property: 1v=v

6. Distributive Property: a(u + v) = au + av


Example



SUBSPACE

A subspace is a subset of a vector space. To be a subspace of vectors the following must be true:

1. One set must be a subset of another set

2. The set must be closed under scalar multiplication

3. The set must be closed under vector addition


Proving one set is a subset of another set

Given sets A and B we say that is is a subset of B if every element of A is also an element of B, that is,

x∈A implies x∈B


Basic Outline of the Proof that A is a subset of B:


· Suppose x ∈ A

1. Say what it means for x to be in A

2. Mathematical details

3. Conclude that x satisfies what it means to be in B


· Conclude x∈B


Example

Let A be the set of scalars divisible by 6 and let B be the even numbers. Prove that A is a subset of B.


· Suppose x ∈ A:

1. What it means for x to be in A: x = 6k for any scalar k

2. x = 2 × (3k)

  3k = C

3. What it means for x to be in B: x = 2C


· Conclude x∈B


Closed Under Scalar Multiplication

A set of vectors is closed under scalar multiplication if for every v∈V and every c∈\mathbb{R} we have cv∈V


Basic Outline of the Proof V is Closed Under Scalar Multiplication:


· Suppose v∈V and c∈\mathbb{R}

1. Say what it means for v to be in V

2. Mathematical details

3. Conclude that cv satisfies what it means to be in V


· Conclude cv∈V


Closed Under Vector Addition

A set of vectors is closed under vector addition if for every v and w ∈ V we have v + w ∈ V


Basic Outline of the Proof V is Closed Under Vector Addition:


· Suppose v and w ∈ V

1. Say what it means for v and w to be in V

2. Mathematical details

3. Conclude that v+ w satisfies what it means to be in V


· Conclude v + w ∈ V


Example

Let V be the set of points in R^2 such that x=y


· Suppose v and w ∈ V

1. What it means for v and w to be in V :

v = (v1, v2) and v1 = v2

w = (w1, w2) and w1 = w2

2. z = v + w = (v1+w1, v2+w2) = (v1+w1, v1+w1)


3. What it means for z to be in V: v1+w1 = v2+w2


· Conclude z = v + w ∈ V




Explanation of how to determine a subspace. Information referenced from Wabash College MA 223, Spring 2011

Alumni Liaison

has a message for current ECE438 students.

Sean Hu, ECE PhD 2009