The Dimension of a Vector Space is equal to the dimension of ‘s Kernel plus its Linear Transformation Rank.
Given a linear transformation whose domain is the Vector Space , we have that
Proof
Assume that , and that at first.
Then will have a Hamel Basis 1.
Since Any linearly independent set can be extended to a Hamel basis, we can extend it to a basis of itself by uniting with vectors outside of its span.
Thus, is a basis for .
Since A linear transformation’s image of a basis spans its image, we have that is a Spanning Set for ─ but note that2
Thus, is spanned by the vectors in . We seek to prove that it is a basis ─ thus, that it is also linearly independent. Thus, we seek to prove that .
Consider the Linear Combination
which implies that ─ thus, it can be written as a linear combination of its basis :
where we invoke that is linearly independent, for which this sum only equals if all coefficients are also .
Thus, is a basis for , and we can conclude that
If , we need only consider a basis for , for which we’ll reach the same conclusion.
Corollaries
References
- Um Curso de Álgebra Linear, Flávio Ulhoa Coelho & Mary Lilian Lourenço. Editora EDUSP.
Footnotes
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Since it will have a linearly independent set, and since Every vector space which has a linearly independent set has a Hamel Basis containing this set. ↩
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Invokes that The image of the union is the union of the images. ↩