Linear Algebra - Column and Null Space

In summary, the conversation discusses the system Ax=b, where A is a 2x2 matrix. The null space and column space of A are found and it is determined that all vectors b that span R2 allow for the system Kx=b to have a solution. It is also determined that for a given b, the system has a unique solution.
  • #1
vwishndaetr
87
0

Homework Statement



Ax=b where,

A = 2 -1
...-1 2

Homework Equations



a) Find Null Space N(A) and Column Space C(A)
b) For which vectors b does the system Kx=b have a solution?
c) How many solution x does the system have for any given b?

The Attempt at a Solution



a)

For Null Space, I set Ax=0, and got the zero vector. No problem with that.
For Column Space, I set Ax=b, and got b = span ( 2 , -1 )
............-1 2
No problem with Column Space either.
Those are two vectors, I am rusty with notation on here.

b) This is simply the Column Space. All vectors b that span R2 allow Kx=b to have a solution. Ni problem with that either.

c) This is where my issue is. For a given b, how many solutions does x have? No solutions? One? Infinitely many?

I am having a hard time sorting this out intuitively. I want to say it will be one solution for a given b, but I can't come to that agreement.
 
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  • #2
Suppose Kx=b has two solutions, Ka1=b and Ka2=b. Subtract the two equations. What can you say about a1-a2 vis a vis a space related to K that it might be in?
 
  • #3
Bit confused about what you mean by vis.
 
  • #4
"vis a vis" means "in relation to".

His point was that if Ax= b and Ay= b then Ax- Ay= b- b or A(x-y)= 0. That is, x- y is a vector in the kernel of A. What did you get for the kernel of A?
 
  • #5
Kernel is related to Null Space correct?

So, since I got the zero vector for Null Space, is the only solution the trivial one?

A(x-y) = 0, where x-y = 0 = N(A) ?
 
  • #6
vwishndaetr said:
Kernel is related to Null Space correct?

So, since I got the zero vector for Null Space, is the only solution the trivial one?

A(x-y) = 0, where x-y = 0 = N(A) ?

Yes. x-y=0 means x=y.
 
  • #7
vwishndaetr said:
Kernel is related to Null Space correct?

So, since I got the zero vector for Null Space, is the only solution the trivial one?

A(x-y) = 0, where x-y = 0 = N(A) ?
"Kernel" is another word for "null space". Sorry, I should have noticed that you used "null space".

Yes, you are correct that the null space for this operator is {0}. So in order that Ax=b= Ay, which is the same as A(x-y)= 0, x- y must be in the null space: x-y= 0 or x= y. So how many different solutions can Ax= b have?
 
  • #8
Please forgive me, but still a wee bit confused.I want to say one solution where x = y = 0.

They way I am thinking is,

Let Az = 0, then z = zero vector.

So, A(x-y) = A(z) = 0

then, x-y = z = 0, so x = y

So infinitely many solutions?

I really want to understand this, because I am a few problems similar so I do not want to just "accept" it. But it feels like I am walking in circles. Maybe it is easier than I what I expect?
 
  • #9
vwishndaetr said:
Please forgive me, but still a wee bit confused.I want to say one solution where x = y = 0.

They way I am thinking is,

Let Az = 0, then z = zero vector.

So, A(x-y) = A(z) = 0

then, x-y = z = 0, so x = y

So infinitely many solutions?

I really want to understand this, because I am a few problems similar so I do not want to just "accept" it. But it feels like I am walking in circles. Maybe it is easier than I what I expect?

The point is that if A(x)=b and A(y)=b, then A(x-y)=0 (since Ax-Ay=b-b), ok so far? If A(x-y)=0 then x-y is in the null space, still ok? Since you've shown the null space is {0}, then x-y=0. So x=y. So if x and y are both solutions, then x-y. Now, how many solutions to Ax=b?
 
  • #10
Dick said:
The point is that if A(x)=b and A(y)=b, then A(x-y)=0 (since Ax-Ay=b-b), ok so far? If A(x-y)=0 then x-y is in the null space, still ok? Since you've shown the null space is {0}, then x-y=0. So x=y. So if x and y are both solutions, then x-y. Now, how many solutions to Ax=b?

ohhhh. Ohhhhh.

Duh.

3 solutions. x is a solution, y is a solution, and x-y = 0 is a solution.

Do I have it now?
 
  • #11
i) 0 isn't a solution to Ax=b (unless b=0, of course). ii) Sure, x is a solution and y is a solution. But x=y! You've shown any two solutions are EQUAL. Take a walk around the block and think this over for a bit. Then count them again.
 
  • #12
vwishndaetr said:
ohhhh. Ohhhhh.

Duh.

3 solutions. x is a solution, y is a solution, and x-y = 0 is a solution.

Do I have it now?
NO! For one thing, x- y= 0 is not a solution to Ax= b, which is what you are working with.
And having said that x- y= 0, it follows that x=y. In other words, x and y are NOT different solutions.
 
  • #13
So that means there is a unique solution for every b.
 
  • #14
Yes. Any problems with that?
 
  • #15
Dick said:
Yes. Any problems with that?

No that is it for me; crystal clear now. Sorry for being so hard-headed.

I am going to do one more, and I will come back to make sure I understand everything correctly. Thanks for the help! This beats any other sources! :)
 

FAQ: Linear Algebra - Column and Null Space

What is the column space in linear algebra?

The column space, also known as the image or range, is the set of all possible linear combinations of the columns of a matrix. This space represents the span of the columns and is a subspace of the vector space in which the matrix operates.

What is the null space in linear algebra?

The null space, also known as the kernel, is the set of all vectors that get mapped to the zero vector by a linear transformation. In other words, it is the set of all solutions to the homogeneous equation Ax = 0, where A is a matrix. This space is a subspace of the vector space in which the matrix operates.

What is the difference between column space and null space?

The column space is the set of all possible outputs of a linear transformation, while the null space is the set of all inputs that produce zero as an output. In other words, the column space represents the "reachable" space, while the null space represents the "unreachable" space.

How can column space and null space be used in practical applications?

Column space and null space have various applications in fields such as computer graphics, data compression, and machine learning. In computer graphics, column space is used to represent the possible transformations of an object, while null space is used to represent the transformations that do not change the object. In data compression, column space and null space can be used to remove redundant information from a dataset. In machine learning, column space and null space can help identify important features and reduce the dimensionality of a dataset.

What is the relationship between column space and null space?

The column space and null space are complementary subspaces, meaning that the dimensions of the two spaces add up to the total dimension of the vector space. This relationship is known as the Rank-Nullity Theorem in linear algebra.

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