Final answer:
The rank theorem states that the dimension of the column space is equal to the dimension of the row space, and the rank of a matrix is equal to the dimension of its column space plus the dimension of its null space. These principles can be verified using the given equations.
Step-by-step explanation:
The rank theorem, also known as the fundamental theorem of linear algebra, states the following:
- The dimension of the column space (ColA) of a matrix A is equal to the dimension of the row space (RowA). In this case, we have dim(ColA1) = dim(RowA1).
- The rank of a matrix A (rank(A)) is equal to the dimension of its column space plus the dimension of its null space (NulA). Here, we have rank(A1) + dim(NulA1) = 3.
We can apply the same reasoning to the second and third statements. Based on the given equation, we have dim(ColA2) = dim(RowA2), and rank(A2) + dim(NulA2) = 5. Similarly, we have dim(ColA3) = dim(RowA3), and rank(A3) + dim(NulA3) = ? (unspecified).