When.com Web Search

Search results

  1. Results From The WOW.Com Content Network
  2. Norm (mathematics) - Wikipedia

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

    In particular, the Euclidean distance in a Euclidean space is defined by a norm on the associated Euclidean vector space, called the Euclidean norm, the 2-norm, or, sometimes, the magnitude or length of the vector. This norm can be defined as the square root of the inner product of a vector with itself.

  3. SymPy - Wikipedia

    en.wikipedia.org/wiki/SymPy

    SymPy is an open-source Python library for symbolic computation. It provides computer algebra capabilities either as a standalone application, as a library to other applications, or live on the web as SymPy Live [2] or SymPy Gamma. [3] SymPy is simple to install and to inspect because it is written entirely in Python with few dependencies.

  4. Normed vector space - Wikipedia

    en.wikipedia.org/wiki/Normed_vector_space

    An example of such a space is the Fréchet space (), whose definition can be found in the article on spaces of test functions and distributions, because its topology is defined by a countable family of norms but it is not a normable space because there does not exist any norm ‖ ‖ on () such that the topology this norm induces is equal to .

  5. Lp space - Wikipedia

    en.wikipedia.org/wiki/Lp_space

    For example, scaling the vector by a positive constant does not change the "norm". Despite these defects as a mathematical norm, the non-zero counting "norm" has uses in scientific computing , information theory , and statistics –notably in compressed sensing in signal processing and computational harmonic analysis .

  6. Schatten norm - Wikipedia

    en.wikipedia.org/wiki/Schatten_norm

    An operator which has a finite Schatten norm is called a Schatten class operator and the space of such operators is denoted by (,). With this norm, S p ( H 1 , H 2 ) {\displaystyle S_{p}(H_{1},H_{2})} is a Banach space, and a Hilbert space for p = 2.

  7. 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.

  8. Symplectic vector space - Wikipedia

    en.wikipedia.org/wiki/Symplectic_vector_space

    A subspace is Lagrangian if and only if it is both isotropic and coisotropic. In a finite-dimensional vector space, a Lagrangian subspace is an isotropic one whose dimension is half that of V. Every isotropic subspace can be extended to a Lagrangian one. Referring to the canonical vector space R 2n above, the subspace spanned by {x 1, y 1} is ...

  9. Operator norm - Wikipedia

    en.wikipedia.org/wiki/Operator_norm

    In mathematics, the operator norm measures the "size" of certain linear operators by assigning each a real number called its operator norm. Formally, it is a norm defined on the space of bounded linear operators between two given normed vector spaces .