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  2. Linear subspace - Wikipedia

    en.wikipedia.org/wiki/Linear_subspace

    If V is a vector space over a field K, a subset W of V is a linear subspace of V if it is a vector space over K for the operations of V.Equivalently, a linear subspace of V is a nonempty subset W such that, whenever w 1, w 2 are elements of W and α, β are elements of K, it follows that αw 1 + βw 2 is in W.

  3. Sequence container (C++) - Wikipedia

    en.wikipedia.org/wiki/Sequence_container_(C++)

    [10] [11] vector<bool> does not meet the requirements for a C++ Standard Library container. For instance, a container<T>::reference must be a true lvalue of type T. This is not the case with vector<bool>::reference, which is a proxy class convertible to bool. [12] Similarly, the vector<bool>::iterator does not yield a bool& when dereferenced.

  4. Vector (C++) - Wikipedia

    en.wikipedia.org/?title=Vector_(C++)&redirect=no

    This page was last edited on 24 June 2014, at 02:53 (UTC).; Text is available under the Creative Commons Attribution-ShareAlike 4.0 License; additional terms may ...

  5. Classifying space for U(n) - Wikipedia

    en.wikipedia.org/wiki/Classifying_space_for_U(n)

    Let F n (C k) be the space of orthonormal families of n vectors in C k and let G n (C k) be the Grassmannian of n-dimensional subvector spaces of C k. The total space of the universal bundle can be taken to be the direct limit of the F n (C k) as k → ∞, while the base space is the direct limit of the G n (C k) as k → ∞.

  6. Quotient space (linear algebra) - Wikipedia

    en.wikipedia.org/wiki/Quotient_space_(linear...

    The first isomorphism theorem for vector spaces says that the quotient space V/ker(T) is isomorphic to the image of V in W. An immediate corollary, for finite-dimensional spaces, is the rank–nullity theorem: the dimension of V is equal to the dimension of the kernel (the nullity of T) plus the dimension of the image (the rank of T).

  7. Direct sum of modules - Wikipedia

    en.wikipedia.org/wiki/Direct_sum_of_modules

    The resulting vector space is called the direct sum of V and W and is usually denoted by a plus symbol inside a circle: It is customary to write the elements of an ordered sum not as ordered pairs ( v , w ), but as a sum v + w .

  8. Transformation matrix - Wikipedia

    en.wikipedia.org/wiki/Transformation_matrix

    If the 4th component of the vector is 0 instead of 1, then only the vector's direction is reflected and its magnitude remains unchanged, as if it were mirrored through a parallel plane that passes through the origin. This is a useful property as it allows the transformation of both positional vectors and normal vectors with the same matrix.

  9. Invariant subspace problem - Wikipedia

    en.wikipedia.org/wiki/Invariant_subspace_problem

    The vector is an eigenvector of the matrix . Every operator on a non-trivial complex finite dimensional vector space has an eigenvector, solving the invariant subspace problem for these spaces. Every operator on a non-trivial complex finite dimensional vector space has an eigenvector, solving the invariant subspace problem for these spaces.