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  2. Linear span - Wikipedia

    en.wikipedia.org/wiki/Linear_span

    For example, in geometry, two linearly independent vectors span a plane. To express that a vector space V is a linear span of a subset S, one commonly uses one of the following phrases: S spans V; S is a spanning set of V; V is spanned or generated by S; S is a generator set or a generating set of V.

  3. Row and column spaces - Wikipedia

    en.wikipedia.org/wiki/Row_and_column_spaces

    because row vectors of A T are transposes of column vectors v k of A. Thus A T x = 0 if and only if x is orthogonal (perpendicular) to each of the column vectors of A. It follows that the left null space (the null space of A T) is the orthogonal complement to the column space of A.

  4. Linear subspace - Wikipedia

    en.wikipedia.org/wiki/Linear_subspace

    for (t 1, t 2, ... , t k) ≠ (u 1, u 2, ... , u k). [note 3] If v 1, ..., v k are linearly independent, then the coordinates t 1, ..., t k for a vector in the span are uniquely determined. A basis for a subspace S is a set of linearly independent vectors whose span is S. The number of elements in a basis is always equal to the geometric ...

  5. Vector space - Wikipedia

    en.wikipedia.org/wiki/Vector_space

    The set of complex numbers C, numbers that can be written in the form x + iy for real numbers x and y where i is the imaginary unit, form a vector space over the reals with the usual addition and multiplication: (x + iy) + (a + ib) = (x + a) + i(y + b) and c ⋅ (x + iy) = (c ⋅ x) + i(c ⋅ y) for real numbers x, y, a, b and c. The various ...

  6. Vector projection - Wikipedia

    en.wikipedia.org/wiki/Vector_projection

    This article uses the convention that vectors are denoted in a bold font (e.g. a 1), and scalars are written in normal font (e.g. a 1). The dot product of vectors a and b is written as a ⋅ b {\displaystyle \mathbf {a} \cdot \mathbf {b} } , the norm of a is written ‖ a ‖, the angle between a and b is denoted θ .

  7. Affine combination - Wikipedia

    en.wikipedia.org/wiki/Affine_combination

    This concept is fundamental in Euclidean geometry and affine geometry, because the set of all affine combinations of a set of points forms the smallest affine space containing the points, exactly as the linear combinations of a set of vectors form their linear span. The affine combinations commute with any affine transformation T in the sense that

  8. Today’s NYT ‘Strands’ Hints, Spangram and Answers for Sunday ...

    www.aol.com/today-nyt-strands-hints-spangram...

    For every 3 non-theme words you find, you earn a hint. Hints show the letters of a theme word. If there is already an active hint on the board, a hint will show that word’s letter order.

  9. Krylov subspace - Wikipedia

    en.wikipedia.org/wiki/Krylov_subspace

    They try to avoid matrix-matrix operations, but rather multiply vectors by the matrix and work with the resulting vectors. Starting with a vector , one computes , then one multiplies that vector by to find and so on. All algorithms that work this way are referred to as Krylov subspace methods; they are among the most successful methods ...