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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: | 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''': | + | 1. '''Communative Property''': u + v = v + u |
2. '''Associative Property''': | 2. '''Associative Property''': | ||
− | a. Of addition: | + | '''·'''a. Of addition: (u + v) + w = u = (v + w) |
− | b. Of multiplication: | + | '''·'''b. Of multiplication: (ab)v = a(bv) |
− | 3. '''Zero Property''': There exist some '''0'''x∈V such that | + | 3. '''Zero Property''': There exist some '''0'''x∈V such that '''0''' + v = v |
− | 4. '''Inverse Property''': For every v∈V there is some w∈V such that | + | 4. '''Inverse Property''': For every v∈V there is some w∈V such that v+w=0 |
− | 5. '''Identity Property''': | + | 5. '''Identity Property''': 1v=v |
− | 6. '''Distributive Property''': | + | 6. '''Distributive Property''': a(u + v) = au + av |
Revision as of 10:24, 3 December 2012
Contents
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:
·a. Of addition: (u + v) + w = u = (v + w)
·b. Of multiplication: (ab)v = a(bv)
3. Zero Property: There exist some 0x∈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
SUBSPACE
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