What Are the Bases for Column and Null Spaces of These Matrices?

In summary, the conversation is about finding bases for the image and kernel of various linear transformations. The first question involves finding a basis for the image of a matrix using the form $\{ \left[\begin{matrix}a \\ b \\ c \\ d\end{matrix}\right] , \left[\begin{matrix}e \\ f \\ g \\ h\end{matrix}\right] \}$. The second question asks for bases of the kernel and image of a linear transformation involving a given matrix. Finally, the third question deals with finding bases for the kernel and range of a linear transformation from a vector space of $2\times 2$ matrices.
  • #1
aidandeno
1
0
Please help me with these three questions. I'm really struggling to understand these concepts and I think that with an understanding of these three, I will be able to tackle the rest before my test on Wednesday.

Thank you.
http://www.texpaste.com/n/g4rwmzzw
1) $$ A = \left[\begin{matrix}
-6 & -4 & -1 \\
-4 & 6 & -5 \\
-6 & -4 & -1 \\
10 & -2 & 6
\end{matrix}\right] $$
Find a basis for the image of $A$ (or, equivalently, for the linear transformation $T(x)=Ax$) in the form

$$\{ \left[\begin{matrix}
a \\ b \\ c \\ d
\end{matrix}\right] , \left[\begin{matrix}
e \\ f \\ g \\ h
\end{matrix}\right] \}$$

2)$$ A = \left[\begin{matrix}
16 & 0 \\
-8 & 0
\end{matrix}\right] $$
Find bases for the kernel and image of $T(\vec{x}) = A \vec{x}. $

A basis for the kernel of $A$ is $$\{ \left[\begin{matrix}
a\\
b
\end{matrix}\right] \}$$
A basis for the image of $A$ is $$\{ \left[\begin{matrix}
c\\
d
\end{matrix}\right] \}$$

3)
Let $V=\mathbb{R}^{2\times 2}$ be the vector space of $2\times 2$ matrices and let $L :V\to V$ be defined by $L(X) = \left[\begin{array}{cc} 10 &2\cr 20 &4 \end{array}\right] X$

A basis for $\ker (L )$ is:$$\{ \left[\begin{matrix}
a & b\\
c & d
\end{matrix}\right] , \left[\begin{matrix}
e & f\\
g & h
\end{matrix}\right]\}$$

A basis for $\text{ran}(L)$ is:$$\{ \left[\begin{matrix}
i & j\\
k & l
\end{matrix}\right] , \left[\begin{matrix}
m & n\\
o & p
\end{matrix}\right]\}$$
 
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  • #2
Hi aidandeno,

Welcome to MHB! :)

Please ask one question per thread and show us what you've done so we know where to help you. Let's do #1.

A basis for the image is a basis for the column space of $A$. What is the rank of $A$? How can we find out the number of linearly independent columns?
 

FAQ: What Are the Bases for Column and Null Spaces of These Matrices?

What is the basis for a column in a matrix?

The basis for a column in a matrix refers to the linearly independent vectors that span the column space of that matrix. They form a set of vectors that can be used to represent all other vectors in that column space.

What is the basis for the null space of a matrix?

The basis for the null space of a matrix refers to the set of all vectors that, when multiplied by that matrix, result in a zero vector. These vectors are also known as the kernel of the matrix.

How is the basis for the column space determined?

The basis for the column space is determined by finding the linearly independent columns of the matrix. These columns form a basis for the column space and can be used to represent all other columns in that space.

What is the significance of the basis for the null space?

The basis for the null space is important because it represents all possible solutions to a homogeneous system of linear equations. It can also be used to find the rank and nullity of a matrix.

Can the basis for the column and null space be the same?

No, the basis for the column and null space cannot be the same. The basis for the column space consists of linearly independent columns, while the basis for the null space consists of linearly independent vectors that result in a zero vector when multiplied by the matrix. These are two distinct sets of vectors.

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