affine combination
Definition
Let V be a vector space over a division ring D. An affine combination of a finite set
of vectors v1,…,vn∈V is a linear combination
of the vectors
k1v1+⋯+knvn |
such that ki∈D subject to the condition k1+⋯+kn=1. In effect, an affine combination is a weighted average of the vectors in question.
For example, v=12v1+12v2 is an affine combination of v1 and v2 provided that the characteristic of D is not 2. v is known as the midpoint of v1 and v2. More generally, if char(D) does not divide m, then
v=1m(v1+⋯+vm) |
is an affine combination of the vi’s. v is the barycenter of v1,…,vn.
Relations with Affine Subspaces
Assume now char(D)=0. Given v1,…,vn∈V, we can form the set A of all affine combinations of the vi’s. We have the following
A is a finite dimensional affine subspace. Conversely, a finite dimensional affine subspace A is the set of all affine combinations of a finite set of vectors in A.
Proof.
Suppose A is the set of affine combinations of v1,…,vn. If n=1, then A is a singleton {v}, so A=0+v, where 0 is the null subspace of V. If n>1, we may pick a non-zero vector v∈A. Define S={a-v∣a∈A}. Then for any s∈S and d∈D, ds=d(a-v)=da+(1-d)v-v. Since da+(1-d)v∈A, ds∈S. If s1,s2∈S, then 12(s1+s2)=12((a1-v)+(a2-v))=12(a1+a2)-v∈S, since 12(a1+a2)∈A. So 12(s1+s2)∈S. Therefore, s1+s2=2(12(s1+s2))∈S. This shows that S is a vector subspace of V and that A=S+v is an affine subspace.
Conversely, let A be a finite dimensional affine subspace. Write A=S+v, where S is a subspace of V. Since dim(S)=dim(A)=n, S has a basis {s1,…,sn}. For each i=1,…,n, define vi=nsi+v. Given a∈A, we have
a | = | s+v=k1s1+⋯+knsn+v | ||
= | k1n(v1-v)+⋯+knn(vn-v)+v | |||
= | k1nv1+⋯+knnvn+(1-k1n-⋯-knn)v. |
From this calculation, it is evident that a is an affine combination of v1,…,vn, and v. ∎
When A is the set of affine combinations of two distinct vectors v,w, we see that A is a line, in the sense that A=S+v, a translate of a one-dimensional subspace S (a line through 0). Every element in A has the form dv+(1-d)w, d∈D. Inspecting the first part of the proof in the previous proposition
, we see that the argument involves no more than two vectors at a time, so the following useful corollary is apparant:
A is an affine subspace iff for every pair of vectors in A, the line formed by the pair is also in A.
Note, however, that the A in the above corollary is not assumed to be finite dimensional.
Remarks.
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•
If one of v1,…,vn is the zero vector, then A coincides with S. In other words, an affine subspace is a vector subspace if it contains the zero vector.
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Given A={k1v1+⋯+knvn∣vi∈V,ki∈D,∑ki=1}, the subset
{k1v1+⋯+knvn∈A∣ki=0} is also an affine subspace.
Affine Independence
Since every element in a finite dimensional affine subspace A is an affine combination of a finite set of vectors in A, we have the similar concept of a spanning set
of an affine subspace. A minimal
spanning set M of an affine subspace is said to be affinely independent. We have the following three equivalent
characterization of an affinely independent subset M of a finite dimensional affine subspace:
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1.
M={v1,…,vn} is affinely independent.
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2.
every element in A can be written as an affine combination of elements in M in a unique fashion.
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3.
for every v∈M, N={vi-v∣v≠vi} is linearly independent
.
Proof.
We will proceed as follows: (1) implies (2) implies (3) implies (1).
(1) implies (2). If a∈A has two distinct representations k1v1+⋯+knvn=a=r1v1+⋯+rnvn, we may assume, say k1≠r1. So k1-r1 is invertible with inverse
t∈D. Then
v1=t(r2-k2)v2+⋯+t(rn-kn)vn. |
Furthermore,
n∑i=2t(ri-ki)=t(n∑i=2ri-n∑i=2ki)=t(1-r1-1+k1)=1. |
So for any b∈A, we have
b=s1v1+⋯+snvn=s1(t(r2-k2)v2+⋯+t(rn-kn)vn)+⋯+snvn. |
The sum of the coefficients is easily seen to be 1, which implies that {v2,…,vn} is a spanning set of A that is smaller than M, a contradiction.
(2) implies (3). Pick v=v1. Suppose 0=s2(v2-v1)+⋯+sn(vn-v1). Expand and we have 0=(-s2-⋯-sn)v1+s2v2+⋯+snvn. So (1-s2-⋯-sn)v1+s2v2+⋯+snvn=v1∈A. By assumption, there is exactly one way to express v1, so we conclude that s2=⋯=sn=0.
(3) implies (1). If M were not minimal, then some v∈M could be expressed as an affine combination of the remaining vectors in M. So suppose v1=k2v2+⋯+knvn. Since ∑ki=1, we can rewrite this as 0=k2(v2-v1)+⋯+kn(vn-v1). Since not all ki=0, N={v2-v1,…,vn-v1} is not linearly independent. ∎
Remarks.
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If {v1,…,vn} is affinely independent set spanning A, then dim(A)=n-1.
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More generally, a set M (not necessarily finite) of vectors is said to be affinely independent if there is a vector v∈M, such that N={w-v∣v≠w∈M} is linearly independent (every finite subset of N is linearly independent). The above three characterizations are still valid in this general setting. However, one must be careful that an affine combination is a finitary operation so that when we take the sum of an infinite
number of vectors, we have to realize that only a finite number of them are non-zero.
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Given any set S of vectors, the affine hull of S is the smallest affine subspace A that contains every vector of S, denoted by Aff(S). Every vector in Aff(S) can be written as an affine combination of vectors in S.
Title | affine combination |
Canonical name | AffineCombination |
Date of creation | 2013-03-22 16:00:13 |
Last modified on | 2013-03-22 16:00:13 |
Owner | CWoo (3771) |
Last modified by | CWoo (3771) |
Numerical id | 19 |
Author | CWoo (3771) |
Entry type | Definition |
Classification | msc 51A15 |
Synonym | affine independent |
Related topic | AffineGeometry |
Related topic | AffineTransformation |
Related topic | ConvexCombination |
Defines | affine independence |
Defines | affinely independent |
Defines | affine hull |