Any vector in the Null space of a matrix A is orthogonal to any vector in the Row space of A
$begingroup$
Let $A$ be a $m times n$ matrix thus $A$ can be represented by the linear transformation $T: mathbb{R}^n to mathbb{R}^m$
Let $v in R(A) implies v in mathbb{R}^n$
If $w in N(A) implies Tw=0$
I want to prove that the inner product $langle v,wrangle=0$ but I don't know how to proceed
linear-algebra functional-analysis proof-writing linear-transformations
$endgroup$
add a comment |
$begingroup$
Let $A$ be a $m times n$ matrix thus $A$ can be represented by the linear transformation $T: mathbb{R}^n to mathbb{R}^m$
Let $v in R(A) implies v in mathbb{R}^n$
If $w in N(A) implies Tw=0$
I want to prove that the inner product $langle v,wrangle=0$ but I don't know how to proceed
linear-algebra functional-analysis proof-writing linear-transformations
$endgroup$
$begingroup$
Hint: Write out in sum form what $A cdot X = 0$ means e.g. like $a_{11} x_1 + ... + a_{1n} x_n = 0$. This is an inner product that is equal to $0$.
$endgroup$
– Story123
Dec 24 '18 at 1:35
add a comment |
$begingroup$
Let $A$ be a $m times n$ matrix thus $A$ can be represented by the linear transformation $T: mathbb{R}^n to mathbb{R}^m$
Let $v in R(A) implies v in mathbb{R}^n$
If $w in N(A) implies Tw=0$
I want to prove that the inner product $langle v,wrangle=0$ but I don't know how to proceed
linear-algebra functional-analysis proof-writing linear-transformations
$endgroup$
Let $A$ be a $m times n$ matrix thus $A$ can be represented by the linear transformation $T: mathbb{R}^n to mathbb{R}^m$
Let $v in R(A) implies v in mathbb{R}^n$
If $w in N(A) implies Tw=0$
I want to prove that the inner product $langle v,wrangle=0$ but I don't know how to proceed
linear-algebra functional-analysis proof-writing linear-transformations
linear-algebra functional-analysis proof-writing linear-transformations
edited Dec 24 '18 at 2:02
Santana Afton
2,7192629
2,7192629
asked Dec 24 '18 at 1:32
Dreamer123Dreamer123
32329
32329
$begingroup$
Hint: Write out in sum form what $A cdot X = 0$ means e.g. like $a_{11} x_1 + ... + a_{1n} x_n = 0$. This is an inner product that is equal to $0$.
$endgroup$
– Story123
Dec 24 '18 at 1:35
add a comment |
$begingroup$
Hint: Write out in sum form what $A cdot X = 0$ means e.g. like $a_{11} x_1 + ... + a_{1n} x_n = 0$. This is an inner product that is equal to $0$.
$endgroup$
– Story123
Dec 24 '18 at 1:35
$begingroup$
Hint: Write out in sum form what $A cdot X = 0$ means e.g. like $a_{11} x_1 + ... + a_{1n} x_n = 0$. This is an inner product that is equal to $0$.
$endgroup$
– Story123
Dec 24 '18 at 1:35
$begingroup$
Hint: Write out in sum form what $A cdot X = 0$ means e.g. like $a_{11} x_1 + ... + a_{1n} x_n = 0$. This is an inner product that is equal to $0$.
$endgroup$
– Story123
Dec 24 '18 at 1:35
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
As you know when we multiply a matrix by a vector we find the dot product of each row of the matrix and the given vector.
Since $T(w)= Aw$ and $w$ is in the null space of $T$, we have $Aw=0.$
Now in order to find $Aw$ you need to find the dot product of each row of $A$ and $w$.
Since $Aw=0$, each element $Aw$ is zero, so the dot product of each row of $A$ and $w$ must be zero.
That implies each vector in the row space is orthogonal to $w$ as well,because vectors in row space are simply linear combinations of row vectors of $A$
$endgroup$
$begingroup$
yes, that is correct
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 4:35
$begingroup$
@ Ted Shifrin Done, thanks for the comment.
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 5:05
add a comment |
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1 Answer
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1 Answer
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active
oldest
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$begingroup$
As you know when we multiply a matrix by a vector we find the dot product of each row of the matrix and the given vector.
Since $T(w)= Aw$ and $w$ is in the null space of $T$, we have $Aw=0.$
Now in order to find $Aw$ you need to find the dot product of each row of $A$ and $w$.
Since $Aw=0$, each element $Aw$ is zero, so the dot product of each row of $A$ and $w$ must be zero.
That implies each vector in the row space is orthogonal to $w$ as well,because vectors in row space are simply linear combinations of row vectors of $A$
$endgroup$
$begingroup$
yes, that is correct
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 4:35
$begingroup$
@ Ted Shifrin Done, thanks for the comment.
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 5:05
add a comment |
$begingroup$
As you know when we multiply a matrix by a vector we find the dot product of each row of the matrix and the given vector.
Since $T(w)= Aw$ and $w$ is in the null space of $T$, we have $Aw=0.$
Now in order to find $Aw$ you need to find the dot product of each row of $A$ and $w$.
Since $Aw=0$, each element $Aw$ is zero, so the dot product of each row of $A$ and $w$ must be zero.
That implies each vector in the row space is orthogonal to $w$ as well,because vectors in row space are simply linear combinations of row vectors of $A$
$endgroup$
$begingroup$
yes, that is correct
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 4:35
$begingroup$
@ Ted Shifrin Done, thanks for the comment.
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 5:05
add a comment |
$begingroup$
As you know when we multiply a matrix by a vector we find the dot product of each row of the matrix and the given vector.
Since $T(w)= Aw$ and $w$ is in the null space of $T$, we have $Aw=0.$
Now in order to find $Aw$ you need to find the dot product of each row of $A$ and $w$.
Since $Aw=0$, each element $Aw$ is zero, so the dot product of each row of $A$ and $w$ must be zero.
That implies each vector in the row space is orthogonal to $w$ as well,because vectors in row space are simply linear combinations of row vectors of $A$
$endgroup$
As you know when we multiply a matrix by a vector we find the dot product of each row of the matrix and the given vector.
Since $T(w)= Aw$ and $w$ is in the null space of $T$, we have $Aw=0.$
Now in order to find $Aw$ you need to find the dot product of each row of $A$ and $w$.
Since $Aw=0$, each element $Aw$ is zero, so the dot product of each row of $A$ and $w$ must be zero.
That implies each vector in the row space is orthogonal to $w$ as well,because vectors in row space are simply linear combinations of row vectors of $A$
edited Dec 24 '18 at 5:03
answered Dec 24 '18 at 2:17
Mohammad Riazi-KermaniMohammad Riazi-Kermani
41.6k42061
41.6k42061
$begingroup$
yes, that is correct
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 4:35
$begingroup$
@ Ted Shifrin Done, thanks for the comment.
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 5:05
add a comment |
$begingroup$
yes, that is correct
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 4:35
$begingroup$
@ Ted Shifrin Done, thanks for the comment.
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 5:05
$begingroup$
yes, that is correct
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 4:35
$begingroup$
yes, that is correct
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 4:35
$begingroup$
@ Ted Shifrin Done, thanks for the comment.
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 5:05
$begingroup$
@ Ted Shifrin Done, thanks for the comment.
$endgroup$
– Mohammad Riazi-Kermani
Dec 24 '18 at 5:05
add a comment |
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$begingroup$
Hint: Write out in sum form what $A cdot X = 0$ means e.g. like $a_{11} x_1 + ... + a_{1n} x_n = 0$. This is an inner product that is equal to $0$.
$endgroup$
– Story123
Dec 24 '18 at 1:35