LINEAR ALGEBRA: Linear Mapping

piano.lisa
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I have the linear mapping Pw(x).
How can I prove that:
||P_w(x)||^2 = \Sigma (<x, x_i>)^2
Where the sum is from i = 1 to k

x is any vector which is an element of R^n

I have tried expanding ||P_w(x)||^2 but it doesn't seem to give me the right side of the equation.
Is there any other method you can suggest?
Thank you.
 
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You can start by defining what P_w is. And the x_i. Since the right hand side is independent of w and the left hand side is not, then it cannot be correct as written. (The dual observation also holds: the LHS is independent of the x_i and the RHS is not.)
 
S = (x1,...,xk) is an orthonormal set in Rn.
W = span{S}
 
Well, what is P_W(x) written with respect to the basis x_1,..,x_n?
 
There are two things I don't understand about this problem. First, when finding the nth root of a number, there should in theory be n solutions. However, the formula produces n+1 roots. Here is how. The first root is simply ##\left(r\right)^{\left(\frac{1}{n}\right)}##. Then you multiply this first root by n additional expressions given by the formula, as you go through k=0,1,...n-1. So you end up with n+1 roots, which cannot be correct. Let me illustrate what I mean. For this...
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