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Proof of the Singular Value Decomposition

110 点作者 beckthompson大约 1 年前

4 条评论

FabHK大约 1 年前
Very nice (though hardly approachable unless you already have a good handle on, say, eigenvalue decomposition, outer products = rank 1 matrices, positive semi-definiteness, etc.).<p>NB: I think many of these linear algebra proofs would benefit (in terms of legibility) if the dimensions of the matrices&#x2F;equations were annotated beneath them. (I created a LaTeX macro for my master&#x27;s thesis to do just that.)
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Lucasoato大约 1 年前
Remember that if you consider the SVD for complex matrixes, you should use the Hermitian transpose and not only the usual transposition (symbol used on that page: A^T). Of course, it&#x27;s the same in this case since it&#x27;s considering real matrixes.
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SpaceManNabs大约 1 年前
I have ran into this blog on my own while looking up the gumbel distribution. this is a very high quality blog. surprisingly, one of my collaborators was also credited on one of the posts. small world. it makes me wanna say the blog is even more high quality than i thought.
enthdegree大约 1 年前
Why is the matrix diagonalizable with an eigendecomposition of that form?
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