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  2. Hilbert matrix - Wikipedia

    en.wikipedia.org/wiki/Hilbert_matrix

    The Hilbert matrix is also totally positive (meaning that the determinant of every submatrix is positive). The Hilbert matrix is an example of a Hankel matrix. It is also a specific example of a Cauchy matrix. The determinant can be expressed in closed form, as a special case of the Cauchy determinant. The determinant of the n × n Hilbert ...

  3. Positive operator - Wikipedia

    en.wikipedia.org/wiki/Positive_operator

    Many authors define a positive operator to be a self-adjoint (or at least symmetric) non-negative operator. We show below that for a complex Hilbert space the self adjointness follows automatically from non-negativity. For a real Hilbert space non-negativity does not imply self adjointness.

  4. POVM - Wikipedia

    en.wikipedia.org/wiki/POVM

    In functional analysis and quantum information science, a positive operator-valued measure (POVM) is a measure whose values are positive semi-definite operators on a Hilbert space. POVMs are a generalization of projection-valued measures (PVM) and, correspondingly, quantum measurements described by POVMs are a generalization of quantum ...

  5. Completely positive map - Wikipedia

    en.wikipedia.org/wiki/Completely_positive_map

    Every *-homomorphism is completely positive.[1]For every linear operator : between Hilbert spaces, the map () (), is completely positive. [2] Stinespring's theorem says that all completely positive maps are compositions of *-homomorphisms and these special maps.

  6. Reproducing kernel Hilbert space - Wikipedia

    en.wikipedia.org/wiki/Reproducing_kernel_Hilbert...

    The main difference is that the reproducing kernel is a symmetric function that is now a positive semi-definite matrix for every , in . More formally, we define a vector-valued RKHS (vvRKHS) as a Hilbert space of functions f : X → R T {\displaystyle f:X\to \mathbb {R} ^{T}} such that for all c ∈ R T {\displaystyle c\in \mathbb {R} ^{T}} and ...

  7. Singular value decomposition - Wikipedia

    en.wikipedia.org/wiki/Singular_value_decomposition

    Specifically, the singular value decomposition of an complex matrix ⁠ ⁠ is a factorization of the form =, where ⁠ ⁠ is an ⁠ ⁠ complex unitary matrix, is an rectangular diagonal matrix with non-negative real numbers on the diagonal, ⁠ ⁠ is an complex unitary matrix, and is the conjugate transpose of ⁠ ⁠. Such decomposition ...

  8. Hilbert space - Wikipedia

    en.wikipedia.org/wiki/Hilbert_space

    A Hilbert space is a vector space equipped with an inner product operation, which allows lengths and angles to be defined. Furthermore, Hilbert spaces are complete, which means that there are enough limits in the space to allow the techniques of calculus to be used. A Hilbert space is a special case of a Banach space.

  9. Spectral theory - Wikipedia

    en.wikipedia.org/wiki/Spectral_theory

    This definition applies to a Banach space, but of course other types of space exist as well; for example, topological vector spaces include Banach spaces, but can be more general. [12] [13] On the other hand, Banach spaces include Hilbert spaces, and it is these spaces that find the greatest application and the richest theoretical results. [14]