Reference resources :https://www.zhihu.com/question/40049682/answer/1420483558
There are two situations :
One 、 That's ok X Column
Is the square of its length .
Two 、 Column X That's ok
It is usually dealt with ( normalization ):
For any vector b , It projects to a The vector on must be :
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About columns X That's ok Proof of projection of :
There are two vectors , hold
stay
Projection notation of
.
This process is obviously a linear transformation , So let's record this linear transformation as : .
So according to its definition, there are :
here It's scalar . that
Nature is represented in the vector
The vector over .
Consider from the triangle rule
vector It can be seen as
The error of the .
It is not difficult to see from the geometric relationship ![[ The formula ]](/img/3a/aa6c2a7d5845d97acbb4d407bb391c+%5Cbot%5Cmathbf%7Be%7D+)
Then it will be transformed into a quantitative relationship
It is not difficult to draw a conclusion from the equivalence relation of the marked red :
Note that the default vectors are column vectors , So scalars can be written directly as :
At this point, let's turn back to linear transformation
That's what's mentioned above Projection matrix The whole process of proof .