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  2. Norm (mathematics) - Wikipedia

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

    A vector space with a specified norm is called a normed vector space. In a similar manner, a vector space with a seminorm is called a seminormed vector space. The term pseudonorm has been used for several related meanings. It may be a synonym of "seminorm". [1]

  3. Normed vector space - Wikipedia

    en.wikipedia.org/wiki/Normed_vector_space

    An inner product space is a normed vector space whose norm is the square root of the inner product of a vector and itself. The Euclidean norm of a Euclidean vector space is a special case that allows defining Euclidean distance by the formula d ( A , B ) = ‖ A B → ‖ . {\displaystyle d(A,B)=\|{\overrightarrow {AB}}\|.}

  4. 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.

  5. 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.

  6. Smith normal form - Wikipedia

    en.wikipedia.org/wiki/Smith_normal_form

    The first goal is to find invertible square matrices and such that the product is diagonal. This is the hardest part of the algorithm. Once diagonality is achieved, it becomes relatively easy to put the matrix into Smith normal form.

  7. 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.

  8. Uniform norm - Wikipedia

    en.wikipedia.org/wiki/Uniform_norm

    Restricting this extended norm to the bounded functions (i.e., the functions with finite above extended norm) yields a (finite-valued) norm, called the uniform norm on . Note that the definition of uniform norm does not rely on any additional structure on the set X {\displaystyle X} , although in practice X {\displaystyle X} is often at least a ...

  9. Operator topologies - Wikipedia

    en.wikipedia.org/wiki/Operator_topologies

    If B is a vector space of linear maps on the vector space A, then σ(A, B) is defined to be the weakest topology on A such that all elements of B are continuous. The norm topology or uniform topology or uniform operator topology is defined by the usual norm ||x|| on B(H). It is stronger than all the other topologies below.