Linear Algebra kernal problem

In summary, the linear map T has a kernel and image that can be defined using the given equations. The standard basis for R^2 is a set of basis vectors that can be used to represent T in matrix form.
  • #1
mrroboto
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Homework Statement



Let T (element of L(R^2,R^2) ) be the linear map T(a,b) = (a+b, 2a +2b)

A) What is the kernal of T

B) What is the image of T

C) Give the matrix for T in the standard basis for R^2

Homework Equations



Kernal of T = {v element of V st T(v) = 0}
Image of T = {w element of W st T(v) = w}

I'm not sure about the matrix


The Attempt at a Solution



I'm really not sure where to go with this. In this case, there are two variable (a,b) instead of 1 variable (v), so I don't know how either the kernal or the image work.

I don't know what standard basis means, and I can't find it in my notes.

Can someone help me?
 
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  • #2
Well T is an element of the dual space and it is a map. you want to find the set of points (a,b) such that T(a,b) = (0,0)

As for the image of T try to visualise what the ap is doing to R2

The standard basis is what we normally use as a set of basis vectors, which ill leave you to find out (its pretty obvious youll get it)
 
  • #3
The key for the standard basis is R^2. It's different for all R^n, so focus on the two
 
Last edited:

1. What is the definition of a kernal in linear algebra?

A kernal in linear algebra is a subspace of a vector space that contains all the vectors that are mapped to the zero vector by a linear transformation. It is also known as the null space.

2. How is the kernal related to linear independence?

The vectors in the kernal are always linearly independent. This is because if any vector in the kernal is a linear combination of other vectors in the kernal, it would result in the zero vector being mapped to the zero vector, which is not allowed in a linear transformation.

3. What is the role of the kernal in solving systems of linear equations?

The kernal is closely related to the solution space of a system of linear equations. If the kernal is empty, the system has a unique solution. If the kernal is non-empty, the system has infinitely many solutions.

4. How can the dimension of the kernal be calculated?

The dimension of the kernal can be calculated by finding the number of free variables in the system of linear equations that represents the kernal. Alternatively, it is also equal to the difference between the number of columns and the rank of the matrix representing the linear transformation.

5. Can the kernal be used to determine if a linear transformation is one-to-one or onto?

Yes, the kernal can be used to determine if a linear transformation is one-to-one or onto. If the kernal is empty, the linear transformation is one-to-one. If the kernal is the entire vector space, the linear transformation is onto. If the kernal is neither empty nor the entire vector space, the linear transformation is neither one-to-one nor onto.

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