Proving Nullspaces: Null(M) = Null((M^T)(M)) | Matrix Homework

  • Thread starter Big-oh
  • Start date
  • Tags
    Matrix
In summary, to prove that Null((M^T)(M)) = Null(M), you need to show that both sets are subsets of each other. This can be done by using the properties of the given matrix M and its transpose, M^T, and showing that for any vector x in Null(M), M^T(Mx)= 0, and for any vector x in Null(M^T(M)), M(x)= 0. Both of these conditions prove that the two sets are equal.
  • #1
Big-oh
5
0

Homework Statement



Given an mxn matrix M, prove that Null((M^T)(M)) = Null(M)

Where M^T is the transpose of the matrix M.

The Attempt at a Solution



I was able to get the first part (Null(M) is a subset of Null((M^T)(M))), but I'm just having trouble proving the other way around. I pick any vector in Null((M^T)(M)), but unsure of what to do after that.
 
Physics news on Phys.org
  • #2
The standard way to prove that to sets, A and B, say, are equal is to prove A is a subset of B then prove that B is a subset of A. And you prove A is a subset of B by starting "if x is in A" and then use the properties of A and B to conclude "x is in B".

Here, the two sets are Null(M) and Null(M^T(M)). If x is in Null(M) then M(x)= 0. It then follows immediately that M^T(Mx)= M^T(0)= 0. That's the easy way. If x is in Null(M^T(M)) then M^T(M(x))= 0. Obviously, if M(x)= 0 we are done. What can you say about non-zero x such that M^t(x)= 0?
 

FAQ: Proving Nullspaces: Null(M) = Null((M^T)(M)) | Matrix Homework

What is a nullspace of a matrix?

A nullspace of a matrix is the set of all vectors that when multiplied by the matrix, results in a zero vector. It is also known as the kernel of the matrix.

How do you find the nullspace of a matrix?

To find the nullspace of a matrix, you need to solve the equation Ax = 0, where A is the matrix and x is the vector of unknowns. The solution to this equation will give you the nullspace of the matrix.

What is the dimension of a nullspace?

The dimension of a nullspace is the number of free variables in the solution to the equation Ax = 0. It is also known as the nullity of the matrix.

Why is the nullspace important?

The nullspace is important because it helps us understand the linear dependence of the columns of a matrix. It also helps in finding the basis of a vector space and solving systems of linear equations.

Can a nullspace contain more than one vector?

Yes, a nullspace can contain more than one vector. In fact, if a matrix has n columns, it can have up to n linearly independent vectors in its nullspace. This means that the nullspace can have a dimension of up to n.

Back
Top