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Expansion and Contraction of the Basis 📂Linear Algebra

Expansion and Contraction of the Basis

Theorem1

Let SS be a finite subset of the finite-dimensional vector space VV.

(a) If SS generates VV but is not a basis of VV, then elements of SS can be appropriately removed to reduce it to a basis of VV.

(b) If SS is linearly independent but not a basis of VV, then elements can be suitably added to SS to extend it to a basis of VV.

Corollary

Let WVW \le V be a subspace of the vector space VV of dimension nn. Let γ={v1,,vk}\gamma = \left\{ \mathbf{v}_{1}, \dots, \mathbf{v}_{k} \right\} be a basis of WW. Then, suitable elements can be added to γ\gamma to extend it to a basis β={v1,,vk,vk+1,,vn}\beta = \left\{ \mathbf{v}_{1}, \dots, \mathbf{v}_{k}, \mathbf{v}_{k+1}, \dots, \mathbf{v}_{n} \right\} of VV.

Proof

(a)

span(S)=V\span(S) = V, but if SS is not a basis of VV, it means that SS is linearly dependent. Therefore, some vector v1\mathbf{v}_{1} in SS can be expressed as a linear combination of the other vectors. By the addition/subtraction theorem, S{v1}S \setminus \left\{ \mathbf{v}_{1} \right\} also generates VV. If Sv1S \setminus {\mathbf{v}_{1}} is linearly independent, the proof is complete. If not linearly independent, the same logic can consider a generating set S{v1,v2}S \setminus \left\{ \mathbf{v}_{1}, \mathbf{v}_{2} \right\} for VV. Repeating this process yields a set that is a basis of VV by removing suitable elements from SS.

(b)

Assume dim(V)=n\dim(V) = n. If SS is linearly independent but not a basis of VV, it means that SS does not generate VV. Then, by the addition/subtraction theorem, adding some vector v1span(S)\mathbf{v}_{1} \notin \span(S) to SS produces S{v1}S \cup \left\{ \mathbf{v}_{1} \right\}, which remains linearly independent. Repeating this process allows for adding suitable vectors to SS to obtain a linearly independent set with a number of elements equal to nn. Since a set in a nn-dimensional vector space that is linearly independent and consists of nn elements is a basis, the proof is complete.


  1. Howard Anton, Elementary Linear Algebra: Aplications Version (12th Edition, 2019), p251-254 ↩︎