Showing that a basis for the ker(A) is in the kernel

In summary, the student attempted to solve an equation system and found that the basis for the kernel was [1;-1;0;1]*w.
  • #1
Jaqi Rose
4
0

Homework Statement


I'm new to this and I was wondering if anyone could help me out

given:

x+z-w=1
y-z+w=1
x+y+z=3

find the coefficient matrix A, the vector of constants B, use Gauss-jordan elimination to solve the system. Find the Rank(A), the Null(A) and a basis for the im(A) and a basis for the ker(A) then verify that the vectors and in the kernel

Homework Equations





The Attempt at a Solution



I reduced the matrix, found the rank to be 3 and the null to be 1, the basis for the

im(A) =( [1;0;1] , [0;1;1] , [1;-1;1] )

then I get to the kernel, I set the equations from the reduced matrix to zero and found

x=w
y=-w
z=0

so the basis for the kernel is [1;-1;0;1] right?

how do I show that that basis is in the kernel?
 
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  • #2
If anything is in the kernel, then it maps to the zero vector. Does this happen?
 
Last edited:
  • #3
I'm not sure what " maps to the zero vector" means, this is my first course in Linear Algerbra ( two class periods so far ) and we don't have a book to work from.

After I reduce the matrix A|B I get

1 0 0 -1 | 0
0 1 0 1 | 2
0 0 1 0 | 1

which gives

x -w = 0
y+w = 2
z=1

i set these to zero ( not sure if that is right ) and then solve the equations for x and y
then i have

X = [x;y;z;w] = [1;-1;0;1]*w

that column vector then becomes my ker(A) right?
 
  • #4
"maps to the zero vector" means that if you plug the basis vector into your system you get zero.

So what I was getting at was - if you plug the basis vector that you got for the kernel in your system, does zero come out? If so, it's a basis for the kernel (assuming you did the rest correctly).
 
  • #5
That a vector v "maps to the zero vector" just means that A*v = 0. You can talk about A as a matrix, but you can also talk about it as function from one vector space to another. That's where the "mapping" terminology comes from.
 
  • #6
yeah, if i take my basis for the ker(A) and plug the vaules back into the original system i get all of the equations to equal zero. is that right then?

thanks for the help by the way :)
 
  • #7
As long as the rest is correct - you have a kernel of dimension 1, you have a nonzero vector in it, so it is a basis. I haven't actually looked at the system itself.
 
  • #8
Thanks!
 

FAQ: Showing that a basis for the ker(A) is in the kernel

What is the definition of a basis for the kernel?

A basis for the kernel of a linear transformation, A, is a set of vectors that span the null space of A and are linearly independent.

Why is it important to show that a basis for the ker(A) is in the kernel?

Showing that a basis for the ker(A) is in the kernel provides a complete characterization of the null space of A and helps to understand the behavior of the linear transformation.

How do you prove that a basis for the ker(A) is in the kernel?

To prove that a basis for the ker(A) is in the kernel, you must first show that the vectors in the basis span the null space of A. Then, you must show that the vectors are linearly independent, meaning that no vector in the basis can be written as a linear combination of the other vectors.

Can there be more than one basis for the ker(A) in the kernel?

Yes, there can be multiple bases for the ker(A) in the kernel. In fact, any set of linearly independent vectors that span the null space of A can be considered a basis for the ker(A).

How does finding a basis for the ker(A) in the kernel relate to solving systems of linear equations?

Finding a basis for the ker(A) in the kernel is equivalent to finding the free variables in a system of linear equations. The basis vectors correspond to the free variables, and the null space of A represents all possible solutions to the system.

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