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  2. Minkowski addition - Wikipedia

    en.wikipedia.org/wiki/Minkowski_addition

    Minkowski sum A + B. For example, if we have two sets A and B, each consisting of three position vectors (informally, three points), representing the vertices of two triangles in , with coordinates

  3. Einstein notation - Wikipedia

    en.wikipedia.org/wiki/Einstein_notation

    The inner product of two vectors is the sum of the products of their corresponding components, with the indices of one vector lowered (see #Raising and lowering indices): , = , = In the case of an orthonormal basis, we have =, and the expression simplifies to: , = =

  4. Dyadics - Wikipedia

    en.wikipedia.org/wiki/Dyadics

    The dyadic product takes in two vectors and returns a second order tensor called a dyadic in this context. A dyadic can be used to contain physical or geometric information, although in general there is no direct way of geometrically interpreting it. The dyadic product is distributive over vector addition, and associative with scalar ...

  5. Dot product - Wikipedia

    en.wikipedia.org/wiki/Dot_product

    Algebraically, the dot product is the sum of the products of the corresponding entries of the two sequences of numbers. Geometrically, it is the product of the Euclidean magnitudes of the two vectors and the cosine of the angle between them. These definitions are equivalent when using Cartesian coordinates.

  6. Direct sum - Wikipedia

    en.wikipedia.org/wiki/Direct_sum

    A topological vector space (TVS) , such as a Banach space, is said to be a topological direct sum of two vector subspaces and if the addition map (,) + is an isomorphism of topological vector spaces (meaning that this linear map is a bijective homeomorphism), in which case and are said to be topological complements in .

  7. 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 ...

  8. Tensor contraction - Wikipedia

    en.wikipedia.org/wiki/Tensor_contraction

    In multilinear algebra, a tensor contraction is an operation on a tensor that arises from the canonical pairing of a vector space and its dual.In components, it is expressed as a sum of products of scalar components of the tensor(s) caused by applying the summation convention to a pair of dummy indices that are bound to each other in an expression.

  9. 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.