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  2. 4D vector - Wikipedia

    en.wikipedia.org/wiki/4D_vector

    In computer science, a 4D vector is a 4-component vector data type.Uses include homogeneous coordinates for 3-dimensional space in computer graphics, and red green blue alpha values for bitmap images with a color and alpha channel (as such they are widely used in computer graphics).

  3. Automatic vectorization - Wikipedia

    en.wikipedia.org/wiki/Automatic_vectorization

    Automatic vectorization, in parallel computing, is a special case of automatic parallelization, where a computer program is converted from a scalar implementation, which processes a single pair of operands at a time, to a vector implementation, which processes one operation on multiple pairs of operands at once.

  4. Vectorization (mathematics) - Wikipedia

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

    Vectorization is a unitary transformation from the space of n×n matrices with the Frobenius (or Hilbert–Schmidt) inner product to C n 2: ⁡ (†) = ⁡ † ⁡ (), where the superscript † denotes the conjugate transpose.

  5. Triple product - Wikipedia

    en.wikipedia.org/wiki/Triple_product

    In geometry and algebra, the triple product is a product of three 3-dimensional vectors, usually Euclidean vectors.The name "triple product" is used for two different products, the scalar-valued scalar triple product and, less often, the vector-valued vector triple product.

  6. Geometric algebra - Wikipedia

    en.wikipedia.org/wiki/Geometric_algebra

    In mathematics, a geometric algebra (also known as a Clifford algebra) is an algebra that can represent and manipulate geometrical objects such as vectors.Geometric algebra is built out of two fundamental operations, addition and the geometric product.

  7. Vector algebra relations - Wikipedia

    en.wikipedia.org/wiki/Vector_algebra_relations

    The following are important identities in vector algebra.Identities that only involve the magnitude of a vector ‖ ‖ and the dot product (scalar product) of two vectors A·B, apply to vectors in any dimension, while identities that use the cross product (vector product) A×B only apply in three dimensions, since the cross product is only defined there.

  8. Parallelogram of force - Wikipedia

    en.wikipedia.org/wiki/Parallelogram_of_force

    Figure 1: Parallelogram construction for adding vectors. This construction has the same result as moving F 2 so its tail coincides with the head of F 1, and taking the net force as the vector joining the tail of F 1 to the head of F 2. This procedure can be repeated to add F 3 to the resultant F 1 + F 2, and so forth.

  9. Linear combination - Wikipedia

    en.wikipedia.org/wiki/Linear_combination

    is the linear combination of vectors and such that = +. In mathematics, a linear combination or superposition is an expression constructed from a set of terms by multiplying each term by a constant and adding the results (e.g. a linear combination of x and y would be any expression of the form ax + by, where a and b are constants).