Find basis for the kernel of linear map

In summary, you need to use the Gram-Schmidt process to make the matrix orthogonal. You can solve for the kernel using a set of linearly independent vectors.
  • #1
jlucas134
22
0
I need help. For this problem, you have to use the Gram-Schmidt process to make it orthogonal.

My trouble is finding the bais for the kernel of the linear map

L: R4 -> R1 defined by L([a,b,c,d)]=a-b-2c+d

I know the dimension of the kernel is 3, but how?
I have tried setting it against the standard basis and that's not right.
I tried solving it by using four vectors with different values, and that keeps giving me a linear dependent vector.

PLEASE HELP!

Am I missing something? I can row reduce and pull out the constants, but I have no idea how to get to the matrix.
 
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  • #2
It's a linear map! L(x1+x2+x3+x4)=L(x1)+L(x2)+L(x3)+L(x4).

Can you see how this helps you?You mave already solved it. Suppose you had a set of linearly independent vectors x1,x,2,x3,x4,...,xk that spans R^n (k necessarily greater than n for our purposes). Then you can take away one of the vectors and see if they still span and if they're linearly independent or not. You can repeat this process until you find a linearly independent set of vectors that span, which of course is going to be a basis.
 
Last edited:
  • #3
I think I have it...if there is constants for artibary numbers then those constants make up the kernal and the other is the range, correct?

SO if the the dim is 4 and the kernel is three, then the range is one...

if I solve it for a=b+2c-d, then the kernal is the constants, b, c, d times the vectors of (a, b, c, d)
 
  • #4
The kernel is {(b + 2c - d, b, c, d) : b, c, d in R}. Do you know how to find the basis from here?
 
  • #5
jlucas134 said:
I need help. For this problem, you have to use the Gram-Schmidt process to make it orthogonal.

My trouble is finding the bais for the kernel of the linear map

L: R4 -> R1 defined by L([a,b,c,d)]=a-b-2c+d

I know the dimension of the kernel is 3, but how?
I have tried setting it against the standard basis and that's not right.
I tried solving it by using four vectors with different values, and that keeps giving me a linear dependent vector.

PLEASE HELP!

Am I missing something? I can row reduce and pull out the constants, but I have no idea how to get to the matrix.

Since you have a single equation, a- b- 2c+ d= 0, you can solve for one variable: for example, d= b+ 2c- a. A standard way of finding a basis is to set each of the variables on the right equal to 1 and the other 0 in turn: If a= 1, b= c= 0, then d= -1; a basis vector is [1, 0, 0, -1]. If b= 1, a= c= 0, then d= 1; a basis vector is [0, 1, 0, 1]. If c= 1, a= b= 0, then d= 2; a basis vector is [0, 0, 1, 2]. Now use Gram-Schmidt to find an orthonormal basis.
 
  • #6
jlucas134 said:
My trouble is finding the bais for the kernel of the linear map

L: R4 -> R1 defined by L([a,b,c,d)]=a-b-2c+d
Just to make sure -- you know that the kernel is the solution space to the equation
L(v) = 0,​
right?
 
  • #7
Got it...

I was making it harder than it was...

I solve for one of the variables, say a...

a=b+2c-d

Then I plug this value into L.

[b+2c-d, b,c,d]

I could set up in aug matrix, but I can pull the constants b, c, d right out to get the kernel basis.

Then my vectors are
u1=[1,1,0,0]
u2= [2,0,1,0]
u3= [-1,0,01]

from here orthogonalize with the GS process.

I do know to be in the kernel it has to be in the zero vector, L(v) = 0, or at least that is how my instructor describes it.

I think I have it from here. Thanks to everyone for their help.
 

What is a kernel of a linear map?

The kernel of a linear map is the set of all inputs that are mapped to the zero vector in the output. In other words, it is the set of all inputs that result in a zero output when the linear map is applied to them.

Why is finding the basis for the kernel important?

Finding the basis for the kernel is important because it helps us understand the structure and properties of the linear map. It also allows us to simplify computations and make further calculations easier.

How do you find the basis for the kernel of a linear map?

To find the basis for the kernel of a linear map, we first need to solve the equation Ax = 0, where A is the matrix representing the linear map and x is a vector of variables. The solutions to this equation will form the basis for the kernel.

Can the basis for the kernel of a linear map be empty?

Yes, it is possible for the basis for the kernel of a linear map to be empty. This means that there are no inputs that result in a zero output when the linear map is applied to them.

What does the dimension of the kernel tell us about the linear map?

The dimension of the kernel tells us about the nullity of the linear map, which is the number of inputs that are mapped to the zero vector. It also gives us information about the rank of the linear map, which is the number of linearly independent inputs that are mapped to non-zero outputs.

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