Prove that rank(A) = rank(A^T)

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SUMMARY

The discussion centers on proving that rank(A) = rank(A^T) for an n x m matrix A where n ≥ m. The proof utilizes the relationship between the image and kernel of matrices, specifically stating that dim((Im A)^c) = dim(ker(A^T)). The argument concludes that since the dimensions of the images are equal, rank(A) must equal rank(A^T). The proof is validated by clarifying the use of terminology and ensuring correct application of linear algebra concepts.

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Homework Statement


Use the below relation to prove that rank(A) = rank(A^T)

Homework Equations


(Im A)^c = ker(A^T) where c is the orthogonal compliment.

The Attempt at a Solution


Let A be an n x m matrix with (n \ge m) and rank(A) = k. Then, rank(A^c) = n-k. From the given relation, rank(ker A^T) must also equal n-k. Thus, rank(A^T) = n - (n-k) = k = rank(A).

Is this a valid argument?
 
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It looks like it's probably correct, but the explanation is a bit confusing because it uses operators in what appear to be non-standard ways. For instance if c denotes orthogonal complement, that is a function whose domain is a vector space, so it cannot be applied to a linear operator, which is what the symbol ##A^c## suggests. Also, I have not seen the rank operator applied to a space rather than to a linear operator, which is what ##rank(ker\ A^T)## suggests. Perhaps it means 'dim'(ension)?
 
Thanks, I agree that my explanation used sloppy terminology. Maybe this is better: Let A be an n x m matrix with n \ge m and rank=k. Then dim((Im A)^c) = m-k = dim(ker(A^T)). Also, dim(ker(A^T)^c)=m-(m-k)=k. But, (ker(A^T))^c = Im(A^T). Therefore, dim(Im(A^T))=k=dim(Im A), and thus rank(A^T)=rank(A)
 

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