In mathematics, a subset S of a vector space V is said to be a basis of V if it satisfies one of the four equivalent conditions:
- S is a minimal generating set of V.
- S is a maximal set of linearly independent vectors.
- S is both a set of linearly independent vectors and a generating set of V.
- every vector in V can be expressed as a linear combination of vectors in S in a unique way.
This definition includes a finiteness condition: a linear combination is always a finite sum of the form a1v1+ ... +anvn.
Using Zorn's lemma, one can show that:
- a) Every vector space has a basis.
- b) Every basis of a vector space has the same cardinality, called the dimension of the vector space.. This result is known as the dimension theorem for vector spaces.
Proof: We have to prove that these 2 vectors are both linearly independent and that they generate R2.
Part I: To prove that they are linearly independent, suppose that there are numbers a,b such that:
- (a-b,a+2b)=(0,0) and a-b=0 and a+2b=0.
- 3b=0 so b=0.
- 3y=b-a, and then
- y=(b-a)/3, and finally
Example III: Let W be the vector space generated by et, e2t. We have already shown they are linearly independent. Then they form a basis for W.
A different notion is that of orthonormal basis of a Hilbert space and some other kinds of bases that occur in Banach spaces or, more generally, in topological vector spaces, where one may define inifinte sums (or series) and express elements of the space as infinite linear combinations of other elements. Ordinary bases are sometimes called Hamel bases in order to distiguish them from these topological concepts, .
- See also :