Orthogonal Projections vs Non-orthogonal projections?

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Orthogonal projections involve projecting a vector onto a set of orthogonal vectors, as demonstrated with the example vectors y, v1, and v2, where v1 and v2 are confirmed to be orthogonal. The projection formula is applied to find the projection of y onto the orthogonal set. In contrast, non-orthogonal projections require different methods since the vectors are not perpendicular, complicating the projection process. A suggested approach for non-orthogonal projections includes finding a unit normal vector derived from the cross product of the vectors. Understanding the distinction between orthogonal and non-orthogonal projections is crucial for accurate vector analysis in linear algebra.
rayzhu52
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Hi everyone,

My Linear Algebra Professor recently had a lecture on Orthogonal projections.

Say for example, we are given the vectors:

y = [3, -1, 1, 13], v1 = [1, -2, -1, 2] and v2 = [-4, 1, 0, 3]

To find the projection of y, we first check is the set v1 and v2 are orthogonal:

v1 • v2 = -4 -2 + 0 + 6 = 0

So we know the set is orthogonal and we can now find the projection of y, or \hat{y}:

\hat{y} =[(y • v1)/(v1 • v1) * v1)
+ [(y • v2)/(v2 • v2) * v2)]
= some value

Now, we covered what it means when a set is non-orthogonal v1 • vn≠ 0,
but what if we are asked to find \hat{y}?

Any form of help would be greatly appreciated!
 
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hi rayzhu52! :smile:

(btw, where did you get • from? use . or · (on a mac, it's alt-shift-9))

(and you've been using too many brackets :wink:)

the easiest way is probably to start by finding the unit normal, a multiple of v1 x v2 :smile:
 
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