5.1 Vector Spaces
A set V is a vector space if:
Closed under addition
Closed under scalar multiplication
Has zero vector
Has additive inverse
Follows 8 vector space axioms
5.2 Linear Combination
Vector v is a linear combination of vectors v1,v2,...,vnv_1, v_2, ...,
v_nv1,v2,...,vn if:
v=c1v1+c2v2+⋯+cnvnv = c_1 v_1 + c_2 v_2 + \cdots + c_n v_nv=c1v1
+c2v2+⋯+cnvn
5.3 Linear Independence
A set is linearly independent if:
c1v1+⋯+cnvn=0⇒c1=c2=⋯=cn=0c_1 v_1 + \cdots + c_n v_n = 0 \
Rightarrow c_1 = c_2 = \cdots = c_n = 0c1v1+⋯+cnvn=0⇒c1=c2=⋯
=cn=0
5.4 Basis and Dimension
Basis = minimal set of linearly independent vectors