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  2. Minkowski addition - Wikipedia

    en.wikipedia.org/wiki/Minkowski_addition

    Minkowski sums act linearly on the perimeter of two-dimensional convex bodies: the perimeter of the sum equals the sum of perimeters. Additionally, if K {\textstyle K} is (the interior of) a curve of constant width , then the Minkowski sum of K {\textstyle K} and of its 180° rotation is a disk.

  3. Euclidean vector - Wikipedia

    en.wikipedia.org/wiki/Euclidean_vector

    The addition of two vectors a and b. This addition method is sometimes called the parallelogram rule because a and b form the sides of a parallelogram and a + b is one of the diagonals. If a and b are bound vectors that have the same base point, this point will also be the base point of a + b.

  4. Vector space - Wikipedia

    en.wikipedia.org/wiki/Vector_space

    The simplest example of a vector space over a field F is the field F itself with its addition viewed as vector addition and its multiplication viewed as scalar multiplication. More generally, all n -tuples (sequences of length n ) ( a 1 , a 2 , … , a n ) {\displaystyle (a_{1},a_{2},\dots ,a_{n})} of elements a i of F form a vector space that ...

  5. Vector notation - Wikipedia

    en.wikipedia.org/wiki/Vector_notation

    The dot product of two vectors u and v can be represented as: In some older literature, the dot product is implied between two vectors written side-by-side. This notation can be confused with the dyadic product between two vectors.

  6. Einstein notation - Wikipedia

    en.wikipedia.org/wiki/Einstein_notation

    In mathematics, especially the usage of linear algebra in mathematical physics and differential geometry, Einstein notation (also known as the Einstein summation convention or Einstein summation notation) is a notational convention that implies summation over a set of indexed terms in a formula, thus achieving brevity.

  7. Dyadics - Wikipedia

    en.wikipedia.org/wiki/Dyadics

    There are numerous ways to multiply two Euclidean vectors. The dot product takes in two vectors and returns a scalar, while the cross product [a] returns a pseudovector. Both of these have various significant geometric interpretations and are widely used in mathematics, physics, and engineering. The dyadic product takes in two vectors and ...

  8. Geometric algebra - Wikipedia

    en.wikipedia.org/wiki/Geometric_algebra

    The cross product of two vectors in dimensions with positive-definite quadratic form is closely related to their exterior product. Most instances of geometric algebras of interest have a nondegenerate quadratic form. If the quadratic form is fully degenerate, the inner product of any two vectors is always zero, and the geometric algebra is then ...

  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).