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I love mountainbike. I hate the Matrix Cookbook.


Aug
30
revised Matrix equation
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Aug
30
answered Matrix equation
Aug
29
revised Are there some algorithms to solve the diagonal matrix $X$ to the following matrix equation?
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Aug
29
revised Are there some algorithms to solve the diagonal matrix $X$ to the following matrix equation?
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Aug
29
answered Are there some algorithms to solve the diagonal matrix $X$ to the following matrix equation?
Aug
28
revised Can this equation have an explicit solution?
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Aug
28
revised Can this equation have an explicit solution?
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Aug
28
answered Can this equation have an explicit solution?
Aug
27
comment Eigenvalues of the sum of two matrices, where one is $B=\operatorname{diag}(1, 0,\dots,0)$
If $B$ is a small matrix that is similar to $diag(x,0,\cdots,0)$, then we can prove a similar result. Now, if $B=diag(x_i)$ then the result does not work; for instance, if the $x_i$ are equal to $x>0$, then the eigenvalues of $A+B$ are $\geq x$ and, consequently, are always $>0$.
Aug
27
comment Transversality in Morse theory, linear algebra version
@ Mads R. Bisgaard , what you found out is incomprehensible.
Aug
26
revised Eigenvalues of the sum of two matrices, where one is $B=\operatorname{diag}(1, 0,\dots,0)$
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Aug
26
comment Eigenvalues of the sum of two matrices, where one is $B=\operatorname{diag}(1, 0,\dots,0)$
Yes, "great" is not the correct word. What I wanted to say is that $B$ must be a small perturbation of $A$.
Aug
25
answered Eigenvalues of the sum of two matrices, where one is $B=\operatorname{diag}(1, 0,\dots,0)$
Aug
23
answered Transversality in Morse theory, linear algebra version
Jul
16
answered Solving $\lambda U^{\dagger}V -\bar{\lambda} V^{\dagger}U = A$
Jun
15
revised How much redundancy resides in an $n \times n$ orthogonal matrix?
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Jun
15
revised How much redundancy resides in an $n \times n$ orthogonal matrix?
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Jun
15
revised How much redundancy resides in an $n \times n$ orthogonal matrix?
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Jun
14
revised How much redundancy resides in an $n \times n$ orthogonal matrix?
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Jun
14
revised How much redundancy resides in an $n \times n$ orthogonal matrix?
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