Math 2.0

statement proposition

Gram–Schmidt vectors are orthogonal

Statement

Let VV be an inner product space over R\R or C\C, and let v1,…,vk∈Vv_1, \dots, v_k \in V be linearly independent. Let u1,…,uku_1, \dots, u_k be the vectors of the Gram–Schmidt process. Then u1,…,uku_1, \dots, u_k are nonzero and pairwise orthogonal, and span⁡(u1,…,uj)=span⁡(v1,…,vj)(1≤j≤k).\operatorname{span}(u_1, \dots, u_j) = \operatorname{span}(v_1, \dots, v_j) \qquad (1 \le j \le k).

Remarks

The proof is by induction on jj: by construction, ⟨uj,ui⟩=0\langle u_j, u_i \rangle = 0 for i<ji < j. The vector uju_j is nonzero, because vjv_j is not in span⁡(v1,…,vj−1)\operatorname{span}(v_1, \dots, v_{j-1}). If the viv_i are only spanning, then the process produces some zero vectors, and dropping them still gives an orthogonal family with the same span.

Explanations

L1 human

The vectors made by Gram–Schmidt are really perpendicular to each other. Also, the first jj new vectors span the same space as the first jj old vectors. So no information is lost at any step.

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  1. Vector space definition
  2. Inner product definition
  3. Linear combination definition
  4. Linear subspace definition
  5. Orthogonal vectors definition
  6. Linear independence definition
  7. Linear span definition
  8. Orthonormal family definition
  9. Gram–Schmidt process concept
  10. Gram–Schmidt vectors are orthogonal statement

Sources

  1. Web https://en.wikipedia.org/wiki/Gram–Schmidt_process, Properties