Null subspace of a single vector

In summary, the conversation discusses the concept of projecting a matrix onto the null space of a vector. The confusion arises when determining which vector, apart from the zero-vector, solves the equation e_kx = 0. The solution is given as x = [1 -1]^T when k = 2. The conversation also clarifies that a vector does not have a null space, but rather a matrix or linear transformation does. The concept of an orthogonal complement is also discussed, with an example given in 3 dimensions. The author of the paper utilizes a projection matrix Z and defines Z1 as Z - (1/n) e*transpose(e), which represents the projection of Z onto the null subspace of e. However, it
  • #1
vix_cse
7
0
Hi:

was wondering if somebody can help me with this I came across in a paper.

$e_k$ is a vector of $k$ $1's. M is a matrix of size n \times k. The author talks about projecting $M$ onto the null space of $e_k$. This is what confuses me. Which $x$ apart from the 0-vector solves e_kx=0.

any help will be appreciated.
 
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  • #2
If k = 2, then x = [1 -1]^T solves e_2^T x = 0.
 
  • #3
I was a bit confused by your reference to "the null space of ek". A vector does not have a "null space", a matrix (or linear transformation) has a "null space". But then, reading doodle's response, it became clear that what you really mean was "orthogonal complement": the set of all vectors whose dot product with ek is 0. The orthogonal complement of a vector in n dimensional space is an n-1 dimensional space.

It might help to think of the situation in 3 dimensions, with an x,y,z, Cartesian coordinate system. The vector e1, the unit vector pointing along the x-axis, has orthogonal complement equal to the yz-plane, the set of all vectors of the form (0,y,z).
 
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  • #4
$e_k$ is a vector of $k$ $1's.
It sounds more like e_k is a 1xk matrix of 1's.
 
  • #5
thanks all for your replies. yeah, it does make sense if i think of it as hallsofivy pointed out : the set of all vectors whose dot product with ek is 0.

this is how the author gets to the part in the paper

Z is a n-by-n projection matrix satisfying Z^2 = Z. e is the same as i mentioned.

define Z1 = Z - (1/n) e*transpose(e)

It is easy to see that Z1 represents the projection of the matrix Z onto the null subspace of e.

I couldn't figure out how it was so easy.

thanks.
 
  • #6
I am still confused. As hallsofivy mentioned, the null subspace of e is a set of vectors. By stating that "Z1 represents the projection of the matrix Z onto the null subspace of e.", Z1 should be vectors. But Z1 is matrix. Can anyone explain this? Thanks.
 

1. What is the null subspace of a single vector?

The null subspace of a single vector is the set of all vectors that, when multiplied by the given vector, result in a zero vector. In other words, it is the set of all vectors that are orthogonal to the given vector.

2. How is the null subspace related to the concept of linear independence?

The null subspace is closely related to the concept of linear independence. A set of vectors is linearly independent if none of the vectors can be written as a linear combination of the others. This means that the null subspace of a single vector is only the zero vector, since no other vector can produce a zero vector when multiplied by it.

3. Can a single vector have a null subspace?

Yes, a single vector can have a null subspace. It is possible for a vector to have an infinite number of vectors that are orthogonal to it, resulting in a null subspace that contains all of these vectors.

4. What is the dimension of the null subspace of a single vector?

The dimension of the null subspace of a single vector is always one less than the dimension of the vector itself. For example, a three-dimensional vector would have a two-dimensional null subspace.

5. How can the null subspace of a single vector be used in practical applications?

The null subspace of a single vector has various applications in fields such as physics, engineering, and computer science. For example, in physics, the null subspace of a force vector can be used to find the equilibrium position in a system. In engineering, the null subspace of a control system can be used to determine the controllability of the system. In computer science, the null subspace of a data vector can be used for data compression and dimensionality reduction.

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