When is the nullspace unique in this case?











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I am given the following:
$$
I - AA^T
$$

is a projection matrix onto the orthogonal complement of $< A >$.



So the nullspace of $I-AA^T$ is the subspace spanned by the set of vectors $x$ such that $(I-AA^T)x = 0$. Since we know the projection matrix projects x onto the orthogonal complement of $<A>$, then I believe this means the nullspace of $I-AA^T$ is $<A>$?



Based on this information, is it possible to determine when $<A>$ is unique?










share|cite|improve this question


















  • 1




    Are some conditions missing? Unless all the singular values of $A$ are zeros or ones, $I-AA^T$ is not a projection.
    – user1551
    Nov 21 at 15:59








  • 1




    It is not a projection since $(I-AA^T)^2 neq I-AA^T$.
    – LinAlg
    Nov 21 at 16:01










  • Hmmmm. I am initially not given any information about $A$. In a later problem, I see that $A$ has orthonormal columns and is not necessarily square.
    – Iamanon
    Nov 21 at 16:09










  • After consulting with a colleague, it seems that we are supposed to assume A has orthonormal columns. So it is a projection matrix based on this condition.
    – Iamanon
    Nov 21 at 16:17















up vote
0
down vote

favorite












I am given the following:
$$
I - AA^T
$$

is a projection matrix onto the orthogonal complement of $< A >$.



So the nullspace of $I-AA^T$ is the subspace spanned by the set of vectors $x$ such that $(I-AA^T)x = 0$. Since we know the projection matrix projects x onto the orthogonal complement of $<A>$, then I believe this means the nullspace of $I-AA^T$ is $<A>$?



Based on this information, is it possible to determine when $<A>$ is unique?










share|cite|improve this question


















  • 1




    Are some conditions missing? Unless all the singular values of $A$ are zeros or ones, $I-AA^T$ is not a projection.
    – user1551
    Nov 21 at 15:59








  • 1




    It is not a projection since $(I-AA^T)^2 neq I-AA^T$.
    – LinAlg
    Nov 21 at 16:01










  • Hmmmm. I am initially not given any information about $A$. In a later problem, I see that $A$ has orthonormal columns and is not necessarily square.
    – Iamanon
    Nov 21 at 16:09










  • After consulting with a colleague, it seems that we are supposed to assume A has orthonormal columns. So it is a projection matrix based on this condition.
    – Iamanon
    Nov 21 at 16:17













up vote
0
down vote

favorite









up vote
0
down vote

favorite











I am given the following:
$$
I - AA^T
$$

is a projection matrix onto the orthogonal complement of $< A >$.



So the nullspace of $I-AA^T$ is the subspace spanned by the set of vectors $x$ such that $(I-AA^T)x = 0$. Since we know the projection matrix projects x onto the orthogonal complement of $<A>$, then I believe this means the nullspace of $I-AA^T$ is $<A>$?



Based on this information, is it possible to determine when $<A>$ is unique?










share|cite|improve this question













I am given the following:
$$
I - AA^T
$$

is a projection matrix onto the orthogonal complement of $< A >$.



So the nullspace of $I-AA^T$ is the subspace spanned by the set of vectors $x$ such that $(I-AA^T)x = 0$. Since we know the projection matrix projects x onto the orthogonal complement of $<A>$, then I believe this means the nullspace of $I-AA^T$ is $<A>$?



Based on this information, is it possible to determine when $<A>$ is unique?







linear-algebra matrices projection projection-matrices






share|cite|improve this question













share|cite|improve this question











share|cite|improve this question




share|cite|improve this question










asked Nov 21 at 15:56









Iamanon

1157




1157








  • 1




    Are some conditions missing? Unless all the singular values of $A$ are zeros or ones, $I-AA^T$ is not a projection.
    – user1551
    Nov 21 at 15:59








  • 1




    It is not a projection since $(I-AA^T)^2 neq I-AA^T$.
    – LinAlg
    Nov 21 at 16:01










  • Hmmmm. I am initially not given any information about $A$. In a later problem, I see that $A$ has orthonormal columns and is not necessarily square.
    – Iamanon
    Nov 21 at 16:09










  • After consulting with a colleague, it seems that we are supposed to assume A has orthonormal columns. So it is a projection matrix based on this condition.
    – Iamanon
    Nov 21 at 16:17














  • 1




    Are some conditions missing? Unless all the singular values of $A$ are zeros or ones, $I-AA^T$ is not a projection.
    – user1551
    Nov 21 at 15:59








  • 1




    It is not a projection since $(I-AA^T)^2 neq I-AA^T$.
    – LinAlg
    Nov 21 at 16:01










  • Hmmmm. I am initially not given any information about $A$. In a later problem, I see that $A$ has orthonormal columns and is not necessarily square.
    – Iamanon
    Nov 21 at 16:09










  • After consulting with a colleague, it seems that we are supposed to assume A has orthonormal columns. So it is a projection matrix based on this condition.
    – Iamanon
    Nov 21 at 16:17








1




1




Are some conditions missing? Unless all the singular values of $A$ are zeros or ones, $I-AA^T$ is not a projection.
– user1551
Nov 21 at 15:59






Are some conditions missing? Unless all the singular values of $A$ are zeros or ones, $I-AA^T$ is not a projection.
– user1551
Nov 21 at 15:59






1




1




It is not a projection since $(I-AA^T)^2 neq I-AA^T$.
– LinAlg
Nov 21 at 16:01




It is not a projection since $(I-AA^T)^2 neq I-AA^T$.
– LinAlg
Nov 21 at 16:01












Hmmmm. I am initially not given any information about $A$. In a later problem, I see that $A$ has orthonormal columns and is not necessarily square.
– Iamanon
Nov 21 at 16:09




Hmmmm. I am initially not given any information about $A$. In a later problem, I see that $A$ has orthonormal columns and is not necessarily square.
– Iamanon
Nov 21 at 16:09












After consulting with a colleague, it seems that we are supposed to assume A has orthonormal columns. So it is a projection matrix based on this condition.
– Iamanon
Nov 21 at 16:17




After consulting with a colleague, it seems that we are supposed to assume A has orthonormal columns. So it is a projection matrix based on this condition.
– Iamanon
Nov 21 at 16:17















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