Orthogonal Projection onto Range of Matrix
up vote
0
down vote
favorite
If $Ainmathbb{R}^{mtimes n}$ and $P_{Rleft(Aright)}$ is the orthogonal projection onto the range of $A$, i.e. $Rleft(Aright)$, then show that $A^{T}P_{Rleft(Aright)}=A^{T}$. So far I have that
$$A^{T}P_{Rleft(Aright)}=A^{T}P_{Rleft(Aright)}^{T}=left(P_{Rleft(Aright)}Aright)^{T}.$$
I am stuck at the last step. How does $P_{Rleft(Aright)}A=A$? My textbook says that if $operatorname{rank}left(Aright)=r$ and $B_{mtimes r}$ is a matrix whose columns form a basis for $Rleft(Aright)$, then $P_{Rleft(Aright)}=Bleft(B^{T}Bright)^{-1}B^{T}$. Additionally, it says that if $operatorname{rank}left(Aright)=n$, then $P_{Rleft(Aright)}=Aleft(A^{T}Aright)^{-1}A^{T}$. It's easy to see that if $operatorname{rank}left(Aright)=n$, then by substituting, we get $P_{Rleft(Aright)}A=A$, but the problem statement does not mention anything about the rank of $A$.
linear-algebra matrices linear-transformations matrix-rank
add a comment |
up vote
0
down vote
favorite
If $Ainmathbb{R}^{mtimes n}$ and $P_{Rleft(Aright)}$ is the orthogonal projection onto the range of $A$, i.e. $Rleft(Aright)$, then show that $A^{T}P_{Rleft(Aright)}=A^{T}$. So far I have that
$$A^{T}P_{Rleft(Aright)}=A^{T}P_{Rleft(Aright)}^{T}=left(P_{Rleft(Aright)}Aright)^{T}.$$
I am stuck at the last step. How does $P_{Rleft(Aright)}A=A$? My textbook says that if $operatorname{rank}left(Aright)=r$ and $B_{mtimes r}$ is a matrix whose columns form a basis for $Rleft(Aright)$, then $P_{Rleft(Aright)}=Bleft(B^{T}Bright)^{-1}B^{T}$. Additionally, it says that if $operatorname{rank}left(Aright)=n$, then $P_{Rleft(Aright)}=Aleft(A^{T}Aright)^{-1}A^{T}$. It's easy to see that if $operatorname{rank}left(Aright)=n$, then by substituting, we get $P_{Rleft(Aright)}A=A$, but the problem statement does not mention anything about the rank of $A$.
linear-algebra matrices linear-transformations matrix-rank
2
If $P$ is projection on a subspace $M$ then $Px=x$ for all $x in M$.
– Kavi Rama Murthy
Nov 16 at 8:54
@KaviRamaMurthy thanks for the hint. I understand this, but I'm not sure how this fact applies.
– Jake
Nov 16 at 9:07
$P_{R(A)}Ax=Ax$ because $Ax in R(A)$.
– Kavi Rama Murthy
Nov 16 at 9:12
add a comment |
up vote
0
down vote
favorite
up vote
0
down vote
favorite
If $Ainmathbb{R}^{mtimes n}$ and $P_{Rleft(Aright)}$ is the orthogonal projection onto the range of $A$, i.e. $Rleft(Aright)$, then show that $A^{T}P_{Rleft(Aright)}=A^{T}$. So far I have that
$$A^{T}P_{Rleft(Aright)}=A^{T}P_{Rleft(Aright)}^{T}=left(P_{Rleft(Aright)}Aright)^{T}.$$
I am stuck at the last step. How does $P_{Rleft(Aright)}A=A$? My textbook says that if $operatorname{rank}left(Aright)=r$ and $B_{mtimes r}$ is a matrix whose columns form a basis for $Rleft(Aright)$, then $P_{Rleft(Aright)}=Bleft(B^{T}Bright)^{-1}B^{T}$. Additionally, it says that if $operatorname{rank}left(Aright)=n$, then $P_{Rleft(Aright)}=Aleft(A^{T}Aright)^{-1}A^{T}$. It's easy to see that if $operatorname{rank}left(Aright)=n$, then by substituting, we get $P_{Rleft(Aright)}A=A$, but the problem statement does not mention anything about the rank of $A$.
linear-algebra matrices linear-transformations matrix-rank
If $Ainmathbb{R}^{mtimes n}$ and $P_{Rleft(Aright)}$ is the orthogonal projection onto the range of $A$, i.e. $Rleft(Aright)$, then show that $A^{T}P_{Rleft(Aright)}=A^{T}$. So far I have that
$$A^{T}P_{Rleft(Aright)}=A^{T}P_{Rleft(Aright)}^{T}=left(P_{Rleft(Aright)}Aright)^{T}.$$
I am stuck at the last step. How does $P_{Rleft(Aright)}A=A$? My textbook says that if $operatorname{rank}left(Aright)=r$ and $B_{mtimes r}$ is a matrix whose columns form a basis for $Rleft(Aright)$, then $P_{Rleft(Aright)}=Bleft(B^{T}Bright)^{-1}B^{T}$. Additionally, it says that if $operatorname{rank}left(Aright)=n$, then $P_{Rleft(Aright)}=Aleft(A^{T}Aright)^{-1}A^{T}$. It's easy to see that if $operatorname{rank}left(Aright)=n$, then by substituting, we get $P_{Rleft(Aright)}A=A$, but the problem statement does not mention anything about the rank of $A$.
linear-algebra matrices linear-transformations matrix-rank
linear-algebra matrices linear-transformations matrix-rank
asked Nov 16 at 8:47
Jake
408312
408312
2
If $P$ is projection on a subspace $M$ then $Px=x$ for all $x in M$.
– Kavi Rama Murthy
Nov 16 at 8:54
@KaviRamaMurthy thanks for the hint. I understand this, but I'm not sure how this fact applies.
– Jake
Nov 16 at 9:07
$P_{R(A)}Ax=Ax$ because $Ax in R(A)$.
– Kavi Rama Murthy
Nov 16 at 9:12
add a comment |
2
If $P$ is projection on a subspace $M$ then $Px=x$ for all $x in M$.
– Kavi Rama Murthy
Nov 16 at 8:54
@KaviRamaMurthy thanks for the hint. I understand this, but I'm not sure how this fact applies.
– Jake
Nov 16 at 9:07
$P_{R(A)}Ax=Ax$ because $Ax in R(A)$.
– Kavi Rama Murthy
Nov 16 at 9:12
2
2
If $P$ is projection on a subspace $M$ then $Px=x$ for all $x in M$.
– Kavi Rama Murthy
Nov 16 at 8:54
If $P$ is projection on a subspace $M$ then $Px=x$ for all $x in M$.
– Kavi Rama Murthy
Nov 16 at 8:54
@KaviRamaMurthy thanks for the hint. I understand this, but I'm not sure how this fact applies.
– Jake
Nov 16 at 9:07
@KaviRamaMurthy thanks for the hint. I understand this, but I'm not sure how this fact applies.
– Jake
Nov 16 at 9:07
$P_{R(A)}Ax=Ax$ because $Ax in R(A)$.
– Kavi Rama Murthy
Nov 16 at 9:12
$P_{R(A)}Ax=Ax$ because $Ax in R(A)$.
– Kavi Rama Murthy
Nov 16 at 9:12
add a comment |
2 Answers
2
active
oldest
votes
up vote
0
down vote
We have $ mathbb R^n=R(A) oplus R(A)^{perp}$ and $R(A)^{perp}=ker(A^T)$.
Let $P=P_{R(A)}$, then we have
$Px=x$ for all $x in R(A)$ and $Px=0$ for all $x in ker(A^T)$.
Hence:
$A^TPx=A^Tx$ for all $x in R(A)$ and $A^TPx=0=A^Tx$ for all $x in ker(A^T)$.
add a comment |
up vote
0
down vote
["] How does $P_{R(A)}A=A$? [."]
$forall xin mathbb R^n, Axin R(A)subseteqmathbb R^m$.- The behavior of $P$ on its range is just identity, i.e. $P_{R(A)}=I_{R(A)}.$ This is can be proved by $P^2=P$, since $P$ is projection.
add a comment |
2 Answers
2
active
oldest
votes
2 Answers
2
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
0
down vote
We have $ mathbb R^n=R(A) oplus R(A)^{perp}$ and $R(A)^{perp}=ker(A^T)$.
Let $P=P_{R(A)}$, then we have
$Px=x$ for all $x in R(A)$ and $Px=0$ for all $x in ker(A^T)$.
Hence:
$A^TPx=A^Tx$ for all $x in R(A)$ and $A^TPx=0=A^Tx$ for all $x in ker(A^T)$.
add a comment |
up vote
0
down vote
We have $ mathbb R^n=R(A) oplus R(A)^{perp}$ and $R(A)^{perp}=ker(A^T)$.
Let $P=P_{R(A)}$, then we have
$Px=x$ for all $x in R(A)$ and $Px=0$ for all $x in ker(A^T)$.
Hence:
$A^TPx=A^Tx$ for all $x in R(A)$ and $A^TPx=0=A^Tx$ for all $x in ker(A^T)$.
add a comment |
up vote
0
down vote
up vote
0
down vote
We have $ mathbb R^n=R(A) oplus R(A)^{perp}$ and $R(A)^{perp}=ker(A^T)$.
Let $P=P_{R(A)}$, then we have
$Px=x$ for all $x in R(A)$ and $Px=0$ for all $x in ker(A^T)$.
Hence:
$A^TPx=A^Tx$ for all $x in R(A)$ and $A^TPx=0=A^Tx$ for all $x in ker(A^T)$.
We have $ mathbb R^n=R(A) oplus R(A)^{perp}$ and $R(A)^{perp}=ker(A^T)$.
Let $P=P_{R(A)}$, then we have
$Px=x$ for all $x in R(A)$ and $Px=0$ for all $x in ker(A^T)$.
Hence:
$A^TPx=A^Tx$ for all $x in R(A)$ and $A^TPx=0=A^Tx$ for all $x in ker(A^T)$.
answered Nov 16 at 9:13
Fred
42.2k1642
42.2k1642
add a comment |
add a comment |
up vote
0
down vote
["] How does $P_{R(A)}A=A$? [."]
$forall xin mathbb R^n, Axin R(A)subseteqmathbb R^m$.- The behavior of $P$ on its range is just identity, i.e. $P_{R(A)}=I_{R(A)}.$ This is can be proved by $P^2=P$, since $P$ is projection.
add a comment |
up vote
0
down vote
["] How does $P_{R(A)}A=A$? [."]
$forall xin mathbb R^n, Axin R(A)subseteqmathbb R^m$.- The behavior of $P$ on its range is just identity, i.e. $P_{R(A)}=I_{R(A)}.$ This is can be proved by $P^2=P$, since $P$ is projection.
add a comment |
up vote
0
down vote
up vote
0
down vote
["] How does $P_{R(A)}A=A$? [."]
$forall xin mathbb R^n, Axin R(A)subseteqmathbb R^m$.- The behavior of $P$ on its range is just identity, i.e. $P_{R(A)}=I_{R(A)}.$ This is can be proved by $P^2=P$, since $P$ is projection.
["] How does $P_{R(A)}A=A$? [."]
$forall xin mathbb R^n, Axin R(A)subseteqmathbb R^m$.- The behavior of $P$ on its range is just identity, i.e. $P_{R(A)}=I_{R(A)}.$ This is can be proved by $P^2=P$, since $P$ is projection.
edited Nov 16 at 16:24
answered Nov 16 at 15:38
614177
416
416
add a comment |
add a comment |
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
StackExchange.ready(
function () {
StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fmath.stackexchange.com%2fquestions%2f3000904%2forthogonal-projection-onto-range-of-matrix%23new-answer', 'question_page');
}
);
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Sign up or log in
StackExchange.ready(function () {
StackExchange.helpers.onClickDraftSave('#login-link');
});
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Sign up using Google
Sign up using Facebook
Sign up using Email and Password
Post as a guest
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
Required, but never shown
2
If $P$ is projection on a subspace $M$ then $Px=x$ for all $x in M$.
– Kavi Rama Murthy
Nov 16 at 8:54
@KaviRamaMurthy thanks for the hint. I understand this, but I'm not sure how this fact applies.
– Jake
Nov 16 at 9:07
$P_{R(A)}Ax=Ax$ because $Ax in R(A)$.
– Kavi Rama Murthy
Nov 16 at 9:12