How does the change of basis theorem work in linear algebra?

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SUMMARY

The change of basis theorem in linear algebra allows for the transformation of coordinate representations between different basis sets. Given two bases B={b1,b2} and C={c1,c2}, the change of coordinate matrix P(C to B) is derived from the C-coordinate vectors of b1 and b2. The relationship is established through the equation [c1 c2][x1]=b1 and [c1 c2][y1]=b2, demonstrating how to convert coordinates from basis C to basis B. The discussion also illustrates this concept with a practical example involving a vector v expressed in both Cartesian and alternative bases.

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bonfire09
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Let B={b1,b2} and C={c1,c2} be basis. Then the change of coordinate matrix P(C to B) involves the C-coordinate vectors of b1 and b2. Let
[b1]c=[x1] and [b2]c=[y1]
...[x2]...[y2].

Then by definition [c1 c2][x1]=b1 and [c1 c2][y1]=b2. I don't get how you can
....... [x2].....[y2]
multiply the matrix with basis set C with the change of coordinate matrix P(C to B) to get back basis set B ?
Can anyone help me understand how the derive the fact that you can take the set C basis and matrix P to get basis b1 and b2? My textbook just says very little about it.

Here is an example of a problem relating to this idea.
There was a problem that stated find a basis {u1,u2,u3} for R^3 such that P is the change of coordinates matrix from{u1,u2,u3} to the basis {v1,v2,v3}? P was given and v1,v2,v3were given as well. I know how to do it but don't get the how it works?
 
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Ok. Let's work in Two Dimensions because writing math text on this forum is slow for me.

Suppose there is a vector v = <x1,x2>. We are used to the regular cartesian basis vectors
{e}_1 = <1,0> and {e}_2 = <0,1> such that

v = &lt;x1,x2&gt;^{T} = x1{e}_1 + x2{e}_2

now let's say we want to express v in a new basis like {f}_1 = <1,1> and {f}_2 = <1,2> such that

v = &lt;y1,y2&gt;^{T} = y1{f}_1 + y2{f}_2

since v is the same vector regardless of how it is represented, we can equate the two basis expressions

v = v

y1{f}_1 + y2{f}_2 = x1{e}_1 + x2{e}_2

<{f}_1,{f}_2>&lt;y1,y2&gt;^{T} = <{e}_1,{e}_2>&lt;x1,x2&gt;^{T}

Let <{f}_1,{f}_2> = F (2x2 Matrix with f basis as columns)
Let <{e}_1,{e}_2> = E (2x2 Matrix with f basis as columns)

Then

F&lt;y1,y2&gt;^{T} = E&lt;x1,x2&gt;^{T}

So

&lt;y1,y2&gt;^{T} = F^{T}E&lt;x1,x2&gt;^{T}

Let P = F^{T}E

Then

&lt;y1,y2&gt;^{T} = P&lt;x1,x2&gt;^{T}

I hope this shows where the logic is coming from. If it is still not clear, let me know, and I will clarify. I will edit this better when I return home.
 
thanks this is what I was looking for. I get it.
 

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