Inverses
... ∗ Your calculator can easily compute the inverse of an n × n matrix, or tell you if the€matrix is singular. ∗ Simply enter the matrix, say as [A] on a TI-84, or as ma on a TI-89. Then ...
... ∗ Your calculator can easily compute the inverse of an n × n matrix, or tell you if the€matrix is singular. ∗ Simply enter the matrix, say as [A] on a TI-84, or as ma on a TI-89. Then ...
Aalborg Universitet Trigonometric bases for matrix weighted Lp-spaces Nielsen, Morten
... case p = 2. This follows from Orlicz’ Theorem, see [21]. However, when we consider T in a space with a matrix weight W with e.g. unbounded spectrum on T, it is not so obvious what happens. In the scalar case, the seminal paper by Hunt, Muckenhoupt, and Wheeden [9] demonstrates that the trigonometric ...
... case p = 2. This follows from Orlicz’ Theorem, see [21]. However, when we consider T in a space with a matrix weight W with e.g. unbounded spectrum on T, it is not so obvious what happens. In the scalar case, the seminal paper by Hunt, Muckenhoupt, and Wheeden [9] demonstrates that the trigonometric ...
Extension of the semidefinite characterization of sum of squares
... the motivating one-dimensional case, this will generally be an intractable constraint, but we can try to find a tractable approximation for it, in the form of f (x) being “sum of squares” with respect to some multiplication of vector-valued functions. This is particularly appealing when K is a symme ...
... the motivating one-dimensional case, this will generally be an intractable constraint, but we can try to find a tractable approximation for it, in the form of f (x) being “sum of squares” with respect to some multiplication of vector-valued functions. This is particularly appealing when K is a symme ...
