How to find a basis for the kernel and image of a linear transformation matrix











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Let $$A=
begin{bmatrix}
0 & 0 & 6 & -18 \
0 & 0 & -1 & 3 \
0 & 0 & -2 & 6 \
end{bmatrix}
$$
Find a basis for the kernel and image of the linear transformation $T$ defined by $T(x) =Ax$.






My question is how do you handle the first 2 columns of A which are all zero's? Does that mean the top 2 values of the basis of the kernel are variables? both zero? The methods I know for calculating the basis for the kernel and image of a transformation matrix are not producing the correct answers in WebWork.










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    Let $$A=
    begin{bmatrix}
    0 & 0 & 6 & -18 \
    0 & 0 & -1 & 3 \
    0 & 0 & -2 & 6 \
    end{bmatrix}
    $$
    Find a basis for the kernel and image of the linear transformation $T$ defined by $T(x) =Ax$.






    My question is how do you handle the first 2 columns of A which are all zero's? Does that mean the top 2 values of the basis of the kernel are variables? both zero? The methods I know for calculating the basis for the kernel and image of a transformation matrix are not producing the correct answers in WebWork.










    share|cite|improve this question


























      up vote
      1
      down vote

      favorite









      up vote
      1
      down vote

      favorite












      Let $$A=
      begin{bmatrix}
      0 & 0 & 6 & -18 \
      0 & 0 & -1 & 3 \
      0 & 0 & -2 & 6 \
      end{bmatrix}
      $$
      Find a basis for the kernel and image of the linear transformation $T$ defined by $T(x) =Ax$.






      My question is how do you handle the first 2 columns of A which are all zero's? Does that mean the top 2 values of the basis of the kernel are variables? both zero? The methods I know for calculating the basis for the kernel and image of a transformation matrix are not producing the correct answers in WebWork.










      share|cite|improve this question
















      Let $$A=
      begin{bmatrix}
      0 & 0 & 6 & -18 \
      0 & 0 & -1 & 3 \
      0 & 0 & -2 & 6 \
      end{bmatrix}
      $$
      Find a basis for the kernel and image of the linear transformation $T$ defined by $T(x) =Ax$.






      My question is how do you handle the first 2 columns of A which are all zero's? Does that mean the top 2 values of the basis of the kernel are variables? both zero? The methods I know for calculating the basis for the kernel and image of a transformation matrix are not producing the correct answers in WebWork.







      linear-algebra linear-transformations






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      edited Oct 9 '17 at 16:21









      Jack

      27.1k1681198




      27.1k1681198










      asked Oct 10 '16 at 2:57









      Aaron

      24125




      24125






















          3 Answers
          3






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          up vote
          0
          down vote













          By elimination, you will end up with
          $$
          begin{bmatrix}
          0 & 0 & 0 & 0 \
          0 & 0 & -1 & 3 \
          0 & 0 & 0 & 0 \
          end{bmatrix}
          $$
          which gives you the dimension of the image of $T$ and the kernel of $T$.



          Now, you can read from the matrix a basis for the image of $T$. On the other hand
          $$
          -x_3+3x_4=0
          $$
          tells you how to find a basis for the kernel of $T$.






          share|cite|improve this answer




























            up vote
            0
            down vote













            Image is spanned on linearly independent columns of matrix $A$, which follows from definition of matrix of linear transformation. To find it do the row reduction of $A^T$ and its nonzero columns span the image, or equivalently, if you row reduce $A$ then columns with pivots will correspond to columns of $A$ that form image of the transformation.
            Kernel is set of vectors $x$ such that $Ax=0$. To find it's base you need to solve system of equations given by $Ax=0$.






            share|cite|improve this answer




























              up vote
              -1
              down vote













              The kernel basis is:



              $$ left[
              begin{array}{cc}
              0&0&1&1/3\
              end{array}
              right]^T, left[
              begin{array}{cc}
              1&0&0&0\
              end{array}
              right]^T, left[
              begin{array}{cc}
              0&1&0&0\
              end{array}
              right]^T$$



              The image basis is:



              $$left[
              begin{array}{cc}
              6&-1&-2\
              end{array}
              right]^T$$






              share|cite|improve this answer





















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                3 Answers
                3






                active

                oldest

                votes








                3 Answers
                3






                active

                oldest

                votes









                active

                oldest

                votes






                active

                oldest

                votes








                up vote
                0
                down vote













                By elimination, you will end up with
                $$
                begin{bmatrix}
                0 & 0 & 0 & 0 \
                0 & 0 & -1 & 3 \
                0 & 0 & 0 & 0 \
                end{bmatrix}
                $$
                which gives you the dimension of the image of $T$ and the kernel of $T$.



                Now, you can read from the matrix a basis for the image of $T$. On the other hand
                $$
                -x_3+3x_4=0
                $$
                tells you how to find a basis for the kernel of $T$.






                share|cite|improve this answer

























                  up vote
                  0
                  down vote













                  By elimination, you will end up with
                  $$
                  begin{bmatrix}
                  0 & 0 & 0 & 0 \
                  0 & 0 & -1 & 3 \
                  0 & 0 & 0 & 0 \
                  end{bmatrix}
                  $$
                  which gives you the dimension of the image of $T$ and the kernel of $T$.



                  Now, you can read from the matrix a basis for the image of $T$. On the other hand
                  $$
                  -x_3+3x_4=0
                  $$
                  tells you how to find a basis for the kernel of $T$.






                  share|cite|improve this answer























                    up vote
                    0
                    down vote










                    up vote
                    0
                    down vote









                    By elimination, you will end up with
                    $$
                    begin{bmatrix}
                    0 & 0 & 0 & 0 \
                    0 & 0 & -1 & 3 \
                    0 & 0 & 0 & 0 \
                    end{bmatrix}
                    $$
                    which gives you the dimension of the image of $T$ and the kernel of $T$.



                    Now, you can read from the matrix a basis for the image of $T$. On the other hand
                    $$
                    -x_3+3x_4=0
                    $$
                    tells you how to find a basis for the kernel of $T$.






                    share|cite|improve this answer












                    By elimination, you will end up with
                    $$
                    begin{bmatrix}
                    0 & 0 & 0 & 0 \
                    0 & 0 & -1 & 3 \
                    0 & 0 & 0 & 0 \
                    end{bmatrix}
                    $$
                    which gives you the dimension of the image of $T$ and the kernel of $T$.



                    Now, you can read from the matrix a basis for the image of $T$. On the other hand
                    $$
                    -x_3+3x_4=0
                    $$
                    tells you how to find a basis for the kernel of $T$.







                    share|cite|improve this answer












                    share|cite|improve this answer



                    share|cite|improve this answer










                    answered Oct 10 '16 at 3:23









                    Jack

                    27.1k1681198




                    27.1k1681198






















                        up vote
                        0
                        down vote













                        Image is spanned on linearly independent columns of matrix $A$, which follows from definition of matrix of linear transformation. To find it do the row reduction of $A^T$ and its nonzero columns span the image, or equivalently, if you row reduce $A$ then columns with pivots will correspond to columns of $A$ that form image of the transformation.
                        Kernel is set of vectors $x$ such that $Ax=0$. To find it's base you need to solve system of equations given by $Ax=0$.






                        share|cite|improve this answer

























                          up vote
                          0
                          down vote













                          Image is spanned on linearly independent columns of matrix $A$, which follows from definition of matrix of linear transformation. To find it do the row reduction of $A^T$ and its nonzero columns span the image, or equivalently, if you row reduce $A$ then columns with pivots will correspond to columns of $A$ that form image of the transformation.
                          Kernel is set of vectors $x$ such that $Ax=0$. To find it's base you need to solve system of equations given by $Ax=0$.






                          share|cite|improve this answer























                            up vote
                            0
                            down vote










                            up vote
                            0
                            down vote









                            Image is spanned on linearly independent columns of matrix $A$, which follows from definition of matrix of linear transformation. To find it do the row reduction of $A^T$ and its nonzero columns span the image, or equivalently, if you row reduce $A$ then columns with pivots will correspond to columns of $A$ that form image of the transformation.
                            Kernel is set of vectors $x$ such that $Ax=0$. To find it's base you need to solve system of equations given by $Ax=0$.






                            share|cite|improve this answer












                            Image is spanned on linearly independent columns of matrix $A$, which follows from definition of matrix of linear transformation. To find it do the row reduction of $A^T$ and its nonzero columns span the image, or equivalently, if you row reduce $A$ then columns with pivots will correspond to columns of $A$ that form image of the transformation.
                            Kernel is set of vectors $x$ such that $Ax=0$. To find it's base you need to solve system of equations given by $Ax=0$.







                            share|cite|improve this answer












                            share|cite|improve this answer



                            share|cite|improve this answer










                            answered Apr 19 '17 at 17:58









                            Tomasz Tarka

                            434211




                            434211






















                                up vote
                                -1
                                down vote













                                The kernel basis is:



                                $$ left[
                                begin{array}{cc}
                                0&0&1&1/3\
                                end{array}
                                right]^T, left[
                                begin{array}{cc}
                                1&0&0&0\
                                end{array}
                                right]^T, left[
                                begin{array}{cc}
                                0&1&0&0\
                                end{array}
                                right]^T$$



                                The image basis is:



                                $$left[
                                begin{array}{cc}
                                6&-1&-2\
                                end{array}
                                right]^T$$






                                share|cite|improve this answer

























                                  up vote
                                  -1
                                  down vote













                                  The kernel basis is:



                                  $$ left[
                                  begin{array}{cc}
                                  0&0&1&1/3\
                                  end{array}
                                  right]^T, left[
                                  begin{array}{cc}
                                  1&0&0&0\
                                  end{array}
                                  right]^T, left[
                                  begin{array}{cc}
                                  0&1&0&0\
                                  end{array}
                                  right]^T$$



                                  The image basis is:



                                  $$left[
                                  begin{array}{cc}
                                  6&-1&-2\
                                  end{array}
                                  right]^T$$






                                  share|cite|improve this answer























                                    up vote
                                    -1
                                    down vote










                                    up vote
                                    -1
                                    down vote









                                    The kernel basis is:



                                    $$ left[
                                    begin{array}{cc}
                                    0&0&1&1/3\
                                    end{array}
                                    right]^T, left[
                                    begin{array}{cc}
                                    1&0&0&0\
                                    end{array}
                                    right]^T, left[
                                    begin{array}{cc}
                                    0&1&0&0\
                                    end{array}
                                    right]^T$$



                                    The image basis is:



                                    $$left[
                                    begin{array}{cc}
                                    6&-1&-2\
                                    end{array}
                                    right]^T$$






                                    share|cite|improve this answer












                                    The kernel basis is:



                                    $$ left[
                                    begin{array}{cc}
                                    0&0&1&1/3\
                                    end{array}
                                    right]^T, left[
                                    begin{array}{cc}
                                    1&0&0&0\
                                    end{array}
                                    right]^T, left[
                                    begin{array}{cc}
                                    0&1&0&0\
                                    end{array}
                                    right]^T$$



                                    The image basis is:



                                    $$left[
                                    begin{array}{cc}
                                    6&-1&-2\
                                    end{array}
                                    right]^T$$







                                    share|cite|improve this answer












                                    share|cite|improve this answer



                                    share|cite|improve this answer










                                    answered Oct 10 '16 at 3:32









                                    Aaron

                                    24125




                                    24125






























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