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  2. Matrix norm - Wikipedia

    en.wikipedia.org/wiki/Matrix_norm

    Suppose a vector norm ‖ ‖ on and a vector norm ‖ ‖ on are given. Any matrix A induces a linear operator from to with respect to the standard basis, and one defines the corresponding induced norm or operator norm or subordinate norm on the space of all matrices as follows: ‖ ‖, = {‖ ‖: ‖ ‖ =} = {‖ ‖ ‖ ‖:} . where denotes the supremum.

  3. Operator norm - Wikipedia

    en.wikipedia.org/wiki/Operator_norm

    Every real -by-matrix corresponds to a linear map from to . Each pair of the plethora of (vector) norms applicable to real vector spaces induces an operator norm for all -by-matrices of real numbers; these induced norms form a subset of matrix norms.

  4. Logarithmic norm - Wikipedia

    en.wikipedia.org/wiki/Logarithmic_norm

    In mathematics, the logarithmic norm is a real-valued functional on operators, and is derived from either an inner product, a vector norm, or its induced operator norm. The logarithmic norm was independently introduced by Germund Dahlquist [ 1 ] and Sergei Lozinskiĭ in 1958, for square matrices .

  5. Norm (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Norm_(mathematics)

    In mathematics, a norm is a function from a real or complex vector space to the non-negative real numbers that behaves in certain ways like the distance from the origin: it commutes with scaling, obeys a form of the triangle inequality, and is zero only at the origin.

  6. Inner product space - Wikipedia

    en.wikipedia.org/wiki/Inner_product_space

    Simply, in coordinates, the inner product is the product of a covector with an vector, yielding a matrix (a scalar), while the outer product is the product of an vector with a covector, yielding an matrix. The outer product is defined for different dimensions, while the inner product requires the same dimension.

  7. Normed vector space - Wikipedia

    en.wikipedia.org/wiki/Normed_vector_space

    A norm induces a distance, called its (norm) induced metric, by the formula (,) = ‖ ‖. which makes any normed vector space into a metric space and a topological vector space. If this metric space is complete then the normed space is a Banach space .

  8. Induced representation - Wikipedia

    en.wikipedia.org/wiki/Induced_representation

    Here φ∈L 2 (G/H) means: the space G/H carries a suitable invariant measure, and since the norm of φ(g) is constant on each left coset of H, we can integrate the square of these norms over G/H and obtain a finite result. The group G acts on the induced representation space by translation, that is, (g.φ)(x)=φ(g −1 x) for g,x∈G and φ∈ ...

  9. Toeplitz matrix - Wikipedia

    en.wikipedia.org/wiki/Toeplitz_matrix

    The induced operator is bounded if and only if the coefficients of the Toeplitz matrix are the Fourier coefficients of some essentially bounded function . In such cases, f {\displaystyle f} is called the symbol of the Toeplitz matrix A {\displaystyle A} , and the spectral norm of the Toeplitz matrix A {\displaystyle A} coincides with the L ∞ ...