Nov 18

Constructing a projector onto a given subspace

Constructing a projector onto a given subspace

Let L be a subspace of R^n. Let k=\dim L\ (\leq n) and fix some basis x^{(1)},...,x^{(k)} in L. Define the matrix X=(x^{(1)},...,x^{(k)}) of size n\times k (the vectors are written as column vectors).

Exercise 1. a) With the above notation, the matrix (X^TX)^{-1} exists. b) The matrix P=X(X^TX)^{-1}X^T exists. c) P is a projector.

Proof. a) The determinant of A=X^TX is not zero by linear independence of the basis vectors, so its inverse A^{-1} exists. We also know that A and its inverse are symmetric:

(1) A^T=A, (A^{-1})^T=A^{-1}.

b) To see that P exists just count the dimensions.

c) Let's prove that P is a projector. (1) allows us to make the proof compact. P is idempotent:

P^2=(XA^{-1}X^T)(XA^{-1}X^T)=XA^{-1}(X^TX)A^{-1}X^T =X(A^{-1}A)A^{-1}X^T=XA^{-1}X^T=P.

P is symmetric:


Exercise 2. P projects onto L: \text{Img}(P)=L.

Proof. First we show that \text{Img}(P)\subseteq L. Put

(2) y=A^{-1}X^Tx,

for any x\in R^n. Then

Px=XA^{-1}X^Tx=Xy=\sum x^{(j)}y_j\in L.

This shows that \text{Img}(P)\subseteq L.

Let's prove the opposite inclusion. Any element of L is of form \sum x^{(j)}y_j with some y. N(X)=\{0\} because we are dealing with a basis. This fact and the general equation N(X)\oplus \text{Img}(X^T)=R^n imply \text{Img}(X^T)=R^n. Hence for any given y there exists x such that Ay=X^Tx. Then (2) is true and, as above, Px=\sum x^{(j)}y_j. We have proved \text{Img}(P)\supseteq L.

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