High School Orthogonal Projections: Same Thing or Not?

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The discussion centers on whether orthogonal projections and general projections are the same concept in linear algebra. Participants clarify that a projection is defined by the property A^2 = A, and emphasize that A typically represents a matrix whose columns form a basis for the subspace, not the projection matrix itself. There is confusion regarding the simplification of matrix equations involving non-square matrices, highlighting that such simplifications are not valid. The conversation concludes with the understanding that if matrices were invertible, the projection would merely return the original vector in R^n. Overall, the distinction between orthogonal projections and general projections is affirmed.
Isaac0427
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Why is the orthogonal projection formula written as ##P_A=A(A^TA)^{-1}A^T## as opposed to ##P_A=(A^T)^{-1}A^T##?
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##\left(A^\tau\right)^{-1}\left(A\right)^\tau=1## which doesn't mean a lot. ##A\left(A^\tau A\right)^{-1}A^\tau=1## which is also meaningless. A projection is generally a transformation for which ##A^2=A## holds.
 
You can't simplify ##(A^TA)^{-1}=A^{-1}(A^T)^{-1}## since ##A## is not a square matrix.

@fresh_42 I think ##A## is a matrix whose columns form a basis for the subspace of the projection, not the projection matrix itself.
 
Infrared said:
You can't simplify (ATA)−1=A−1(AT)−1 since A is not a square matrix.
Ah, that's what I was missing. Ok, thank you.
 
Infrared said:
@fresh_42 I think A is a matrix whose columns form a basis for the subspace of the projection, not the projection matrix itself.
And yes. I see though that it would all be meaningless if they were invertible matrices, as then the span of A would be all of ##\mathbb{R}^n##, and a vector in ##\mathbb{R}^n##'s projection onto ##\mathbb{R}^n## is just itself.
 
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