Math 2.0

statement proposition

Coordinates in an orthonormal basis

Statement

Let VV be a finite-dimensional inner product space over R\R or C\C, and let (e1,…,en)(e_1, \dots, e_n) be an orthonormal basis of VV. Then, for each v∈Vv \in V, v=∑i=1n⟨v,ei⟩ ei.v = \sum_{i=1}^{n} \langle v, e_i \rangle\, e_i. So the coordinates of vv in this basis are the inner products ⟨v,ei⟩\langle v, e_i \rangle.

Remarks

If v=∑jajejv = \sum_j a_j e_j, then ⟨v,ei⟩=∑jaj⟨ej,ei⟩=ai\langle v, e_i \rangle = \sum_j a_j \langle e_j, e_i \rangle = a_i. For the basis 12(1,1)\frac{1}{\sqrt 2}(1, 1), 12(1,−1)\frac{1}{\sqrt 2}(1, -1) of R2\R^2, the vector (3,1)(3, 1) has the coordinates 4/24/\sqrt 2 and 2/22/\sqrt 2. With the convention of linearity in the second argument, the coefficient is written ⟨ei,v⟩\langle e_i, v \rangle.

Explanations

L1 human

In an orthonormal basis, we find each coordinate of a vector with one inner product. This is much easier than solving a linear system. It is the finite-dimensional form of a Fourier expansion.

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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. Spanning set definition
  10. Basis definition
  11. Orthonormal basis definition
  12. Coordinates in an orthonormal basis statement

Sources

  1. Web https://en.wikipedia.org/wiki/Orthonormal_basis, Basic formula