column space having non-linear combinations of basis vectors

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I have a matrix $A_3x3$ whose basis for the column space are $a_1=(2,2,5)$, $a_2=(9,5,3)$ and $a_3=(3,6,1)$. If these are the basis for the column space, then column space can always be generated by linear combination of these basis vectors. Right?
Now, here is what I did.
I went for a non-linear combination of these basis vectors given by $a_1^2+a_2+a_3^3$ which is equal to $(40,225,29)$. Now since, $(40,225,29)$ is a non-linear combination of basis vectors, I should not be able to get this by linear combination of basis vectors. To verify this I tried to get the coefficients $x_1,x_2$ and $x_3$ such that $x_1(2,2,5)+x_2(9,5,3)+x_3(3,6,1) = (40,225,29)$. Surprisingly, I am getting a consistent solution.
Why is this discrepancy ? By definition the above system should have been inconsistent.
Any suggestions ?
linear-algebra vector-spaces vectors
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up vote
0
down vote
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I have a matrix $A_3x3$ whose basis for the column space are $a_1=(2,2,5)$, $a_2=(9,5,3)$ and $a_3=(3,6,1)$. If these are the basis for the column space, then column space can always be generated by linear combination of these basis vectors. Right?
Now, here is what I did.
I went for a non-linear combination of these basis vectors given by $a_1^2+a_2+a_3^3$ which is equal to $(40,225,29)$. Now since, $(40,225,29)$ is a non-linear combination of basis vectors, I should not be able to get this by linear combination of basis vectors. To verify this I tried to get the coefficients $x_1,x_2$ and $x_3$ such that $x_1(2,2,5)+x_2(9,5,3)+x_3(3,6,1) = (40,225,29)$. Surprisingly, I am getting a consistent solution.
Why is this discrepancy ? By definition the above system should have been inconsistent.
Any suggestions ?
linear-algebra vector-spaces vectors
Note that using the notation $a^2$ for coordinate wise square of a vector $ainmathbb R^3$ is non-standard and should be explained when used. The same notation is often used to denote the dot product of $a$ with itself, which is a number instead of a vector.
â Christoph
Sep 3 at 7:33
@Christoph It meant that the entries in the columns are squared...
â Upendra Pratap Singh
Sep 3 at 7:40
add a comment |Â
up vote
0
down vote
favorite
up vote
0
down vote
favorite
I have a matrix $A_3x3$ whose basis for the column space are $a_1=(2,2,5)$, $a_2=(9,5,3)$ and $a_3=(3,6,1)$. If these are the basis for the column space, then column space can always be generated by linear combination of these basis vectors. Right?
Now, here is what I did.
I went for a non-linear combination of these basis vectors given by $a_1^2+a_2+a_3^3$ which is equal to $(40,225,29)$. Now since, $(40,225,29)$ is a non-linear combination of basis vectors, I should not be able to get this by linear combination of basis vectors. To verify this I tried to get the coefficients $x_1,x_2$ and $x_3$ such that $x_1(2,2,5)+x_2(9,5,3)+x_3(3,6,1) = (40,225,29)$. Surprisingly, I am getting a consistent solution.
Why is this discrepancy ? By definition the above system should have been inconsistent.
Any suggestions ?
linear-algebra vector-spaces vectors
I have a matrix $A_3x3$ whose basis for the column space are $a_1=(2,2,5)$, $a_2=(9,5,3)$ and $a_3=(3,6,1)$. If these are the basis for the column space, then column space can always be generated by linear combination of these basis vectors. Right?
Now, here is what I did.
I went for a non-linear combination of these basis vectors given by $a_1^2+a_2+a_3^3$ which is equal to $(40,225,29)$. Now since, $(40,225,29)$ is a non-linear combination of basis vectors, I should not be able to get this by linear combination of basis vectors. To verify this I tried to get the coefficients $x_1,x_2$ and $x_3$ such that $x_1(2,2,5)+x_2(9,5,3)+x_3(3,6,1) = (40,225,29)$. Surprisingly, I am getting a consistent solution.
Why is this discrepancy ? By definition the above system should have been inconsistent.
Any suggestions ?
linear-algebra vector-spaces vectors
linear-algebra vector-spaces vectors
asked Sep 3 at 7:05
Upendra Pratap Singh
1063
1063
Note that using the notation $a^2$ for coordinate wise square of a vector $ainmathbb R^3$ is non-standard and should be explained when used. The same notation is often used to denote the dot product of $a$ with itself, which is a number instead of a vector.
â Christoph
Sep 3 at 7:33
@Christoph It meant that the entries in the columns are squared...
â Upendra Pratap Singh
Sep 3 at 7:40
add a comment |Â
Note that using the notation $a^2$ for coordinate wise square of a vector $ainmathbb R^3$ is non-standard and should be explained when used. The same notation is often used to denote the dot product of $a$ with itself, which is a number instead of a vector.
â Christoph
Sep 3 at 7:33
@Christoph It meant that the entries in the columns are squared...
â Upendra Pratap Singh
Sep 3 at 7:40
Note that using the notation $a^2$ for coordinate wise square of a vector $ainmathbb R^3$ is non-standard and should be explained when used. The same notation is often used to denote the dot product of $a$ with itself, which is a number instead of a vector.
â Christoph
Sep 3 at 7:33
Note that using the notation $a^2$ for coordinate wise square of a vector $ainmathbb R^3$ is non-standard and should be explained when used. The same notation is often used to denote the dot product of $a$ with itself, which is a number instead of a vector.
â Christoph
Sep 3 at 7:33
@Christoph It meant that the entries in the columns are squared...
â Upendra Pratap Singh
Sep 3 at 7:40
@Christoph It meant that the entries in the columns are squared...
â Upendra Pratap Singh
Sep 3 at 7:40
add a comment |Â
1 Answer
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2
down vote
Let me do a quick computation to check what does $a_1, a_2, a_3$ span
octave:1> A = [2 2 5; 9 5 3; 3 6 1]
A =
2 2 5
9 5 3
3 6 1
octave:2> rref(A)
ans =
1 0 0
0 1 0
0 0 1
It turns out that it spans $mathbbR^3$, hence anything in $mathbbR^3$ can be written as linear combination of those vectors.
Being a basis of a vector space doesn't say anything about whether it can span any non-linear transform of those three vectors. It can certainly cover its linear combination, but it doesn't guarantee whether it can do so for a particular non-linear combination. After all, a vector that is obtained by a non-linear transform could have been obtained by a linear combination as well.
add a comment |Â
1 Answer
1
active
oldest
votes
1 Answer
1
active
oldest
votes
active
oldest
votes
active
oldest
votes
up vote
2
down vote
Let me do a quick computation to check what does $a_1, a_2, a_3$ span
octave:1> A = [2 2 5; 9 5 3; 3 6 1]
A =
2 2 5
9 5 3
3 6 1
octave:2> rref(A)
ans =
1 0 0
0 1 0
0 0 1
It turns out that it spans $mathbbR^3$, hence anything in $mathbbR^3$ can be written as linear combination of those vectors.
Being a basis of a vector space doesn't say anything about whether it can span any non-linear transform of those three vectors. It can certainly cover its linear combination, but it doesn't guarantee whether it can do so for a particular non-linear combination. After all, a vector that is obtained by a non-linear transform could have been obtained by a linear combination as well.
add a comment |Â
up vote
2
down vote
Let me do a quick computation to check what does $a_1, a_2, a_3$ span
octave:1> A = [2 2 5; 9 5 3; 3 6 1]
A =
2 2 5
9 5 3
3 6 1
octave:2> rref(A)
ans =
1 0 0
0 1 0
0 0 1
It turns out that it spans $mathbbR^3$, hence anything in $mathbbR^3$ can be written as linear combination of those vectors.
Being a basis of a vector space doesn't say anything about whether it can span any non-linear transform of those three vectors. It can certainly cover its linear combination, but it doesn't guarantee whether it can do so for a particular non-linear combination. After all, a vector that is obtained by a non-linear transform could have been obtained by a linear combination as well.
add a comment |Â
up vote
2
down vote
up vote
2
down vote
Let me do a quick computation to check what does $a_1, a_2, a_3$ span
octave:1> A = [2 2 5; 9 5 3; 3 6 1]
A =
2 2 5
9 5 3
3 6 1
octave:2> rref(A)
ans =
1 0 0
0 1 0
0 0 1
It turns out that it spans $mathbbR^3$, hence anything in $mathbbR^3$ can be written as linear combination of those vectors.
Being a basis of a vector space doesn't say anything about whether it can span any non-linear transform of those three vectors. It can certainly cover its linear combination, but it doesn't guarantee whether it can do so for a particular non-linear combination. After all, a vector that is obtained by a non-linear transform could have been obtained by a linear combination as well.
Let me do a quick computation to check what does $a_1, a_2, a_3$ span
octave:1> A = [2 2 5; 9 5 3; 3 6 1]
A =
2 2 5
9 5 3
3 6 1
octave:2> rref(A)
ans =
1 0 0
0 1 0
0 0 1
It turns out that it spans $mathbbR^3$, hence anything in $mathbbR^3$ can be written as linear combination of those vectors.
Being a basis of a vector space doesn't say anything about whether it can span any non-linear transform of those three vectors. It can certainly cover its linear combination, but it doesn't guarantee whether it can do so for a particular non-linear combination. After all, a vector that is obtained by a non-linear transform could have been obtained by a linear combination as well.
edited Sep 3 at 7:32
answered Sep 3 at 7:26
Siong Thye Goh
82.2k1456104
82.2k1456104
add a comment |Â
add a comment |Â
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Note that using the notation $a^2$ for coordinate wise square of a vector $ainmathbb R^3$ is non-standard and should be explained when used. The same notation is often used to denote the dot product of $a$ with itself, which is a number instead of a vector.
â Christoph
Sep 3 at 7:33
@Christoph It meant that the entries in the columns are squared...
â Upendra Pratap Singh
Sep 3 at 7:40