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  2. Krylov subspace - Wikipedia

    en.wikipedia.org/wiki/Krylov_subspace

    Many linear dynamical system tests in control theory, especially those related to controllability and observability, involve checking the rank of the Krylov subspace. These tests are equivalent to finding the span of the Gramians associated with the system/output maps so the uncontrollable and unobservable subspaces are simply the orthogonal ...

  3. Linear subspace - Wikipedia

    en.wikipedia.org/wiki/Linear_subspace

    In mathematics, and more specifically in linear algebra, a linear subspace or vector subspace [1] [note 1] is a vector space that is a subset of some larger vector space. A linear subspace is usually simply called a subspace when the context serves to distinguish it from other types of subspaces .

  4. Controlled invariant subspace - Wikipedia

    en.wikipedia.org/wiki/Controlled_invariant_subspace

    A subspace V ⊂ R n is a controlled invariant subspace if and only if AV ⊂ V + Im B. If V is a controlled invariant subspace, then there exists a matrix K such that the input u(t) = Kx(t) keeps the state within V; this is a simple feedback control (Ghosh 1985, Thm 1.1).

  5. Linear code - Wikipedia

    en.wikipedia.org/wiki/Linear_code

    Codes in general are often denoted by the letter C, and a code of length n and of rank k (i.e., having n code words in its basis and k rows in its generating matrix) is generally referred to as an (n, k) code. Linear block codes are frequently denoted as [n, k, d] codes, where d refers to the code's minimum Hamming distance between any two code ...

  6. Cyclic subspace - Wikipedia

    en.wikipedia.org/wiki/Cyclic_subspace

    The cyclic subspace associated with a vector v in a vector space V and a linear transformation T of V is called the T-cyclic subspace generated by v. The concept of a cyclic subspace is a basic component in the formulation of the cyclic decomposition theorem in linear algebra.

  7. Multilinear subspace learning - Wikipedia

    en.wikipedia.org/wiki/Multilinear_subspace_learning

    Linear subspace learning algorithms are traditional dimensionality reduction techniques that are well suited for datasets that are the result of varying a single causal factor. Unfortunately, they often become inadequate when dealing with datasets that are the result of multiple causal factors. .

  8. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    In linear algebra, the column space (also called the range or image) of a matrix A is the span (set of all possible linear combinations) of its column vectors. The column space of a matrix is the image or range of the corresponding matrix transformation .

  9. Subspace - Wikipedia

    en.wikipedia.org/wiki/Subspace

    Linear subspace, in linear algebra, a subset of a vector space that is closed under addition and scalar multiplication; Flat (geometry), a Euclidean subspace; Affine subspace, a geometric structure that generalizes the affine properties of a flat; Projective subspace, a geometric structure that generalizes a linear subspace of a vector space