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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. 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 ...

  4. Spectral theory - Wikipedia

    en.wikipedia.org/wiki/Spectral_theory

    There have been three main ways to formulate spectral theory, each of which find use in different domains. After Hilbert's initial formulation, the later development of abstract Hilbert spaces and the spectral theory of single normal operators on them were well suited to the requirements of physics, exemplified by the work of von Neumann. [5]

  5. Kernel embedding of distributions - Wikipedia

    en.wikipedia.org/wiki/Kernel_embedding_of...

    Let denote a random variable with domain and distribution .Given a symmetric, positive-definite kernel: the Moore–Aronszajn theorem asserts the existence of a unique RKHS on (a Hilbert space of functions : equipped with an inner product , and a norm ‖ ‖) for which is a reproducing kernel, i.e., in which the element (,) satisfies the reproducing property

  6. Kernel principal component analysis - Wikipedia

    en.wikipedia.org/wiki/Kernel_principal_component...

    which represents the inner product space (see Gramian matrix) of the otherwise intractable feature space. The dual form that arises in the creation of a kernel allows us to mathematically formulate a version of PCA in which we never actually solve the eigenvectors and eigenvalues of the covariance matrix in the Φ ( x ) {\displaystyle \Phi ...

  7. Compact operator on Hilbert space - Wikipedia

    en.wikipedia.org/wiki/Compact_operator_on...

    In the mathematical discipline of functional analysis, the concept of a compact operator on Hilbert space is an extension of the concept of a matrix acting on a finite-dimensional vector space; in Hilbert space, compact operators are precisely the closure of finite-rank operators (representable by finite-dimensional matrices) in the topology induced by the operator norm.

  8. Dilation (operator theory) - Wikipedia

    en.wikipedia.org/wiki/Dilation_(operator_theory)

    In operator theory, a dilation of an operator T on a Hilbert space H is an operator on a larger Hilbert space K, whose restriction to H composed with the orthogonal projection onto H is T. More formally, let T be a bounded operator on some Hilbert space H, and H be a subspace of a larger Hilbert space H' . A bounded operator V on H' is a ...

  9. Hilbert system - Wikipedia

    en.wikipedia.org/wiki/Hilbert_system

    [6] [7] Every Hilbert system is an axiomatic system, which is used by many authors as a sole less specific term to declare their Hilbert systems, [8] [9] [10] without mentioning any more specific terms. In this context, "Hilbert systems" are contrasted with natural deduction systems, [3] in which no axioms are used, only inference rules.