Orthonormal Bases: Determining Coefficients for Arbitrary Vector

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SUMMARY

This discussion focuses on the determination of coefficients for arbitrary vectors expressed in terms of an orthonormal basis in vector space V. It highlights the mathematical expression of a vector v as a linear combination of basis elements using the inner product, specifically e1 + ... + en. The geometric interpretation of this process is clarified through the relationship between the dot product and the coefficients derived from the inner product, emphasizing that the linear operator A defined by Av = ∑i=1n ⟨v, ei⟩ ei retains the original vector v, confirming that A = I.

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  • Understanding of vector spaces and basis elements
  • Familiarity with inner products and dot products
  • Knowledge of orthonormal bases and their properties
  • Basic concepts of linear operators in linear algebra
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mrxtothaz
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If we have a vector that can be expressed in terms of some finite list of basis elements. If we have an orthonormal basis for a vector space V, then a vector v can be expressed as <v,e1>e1 +...+ <v,en>en. This appears to be widely used for many results (such as Gram-Schmidt), but the motivation for this is not clear to me. Not only that, I don't understand why this is the case (geometrically).

Obtaining the coefficients for a given vector (in terms of an orthonormal basis) using the inner product of the vector v with each basis element... why does this work?
 
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If you consider the version of the dot product involving cosine, v\cdot e_{1}=|v||e_{1}|cos\theta=|v|cos\theta because e_{1} is a unit vector. This is just the "e_1 component" of v (rather than the x or y component of v).
I included a poorly done illustration in Paint.
 

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It works because it works on basis vectors. Define the linear operator A by
Av = \sum_{i=1}^n \langle v, e_i \rangle e_i.
Then for any k,
Ae_k = \sum_{i=1}^n \langle e_k, e_i \rangle e_i<br /> = \sum_{i=1}^n \delta_{ki} e_i = e_k.
It follows that A = I, so Av = v for any v.
 

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