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  2. Dot product - Wikipedia

    en.wikipedia.org/wiki/Dot_product

    The length of a vector is defined as the square root of the dot product of the vector by itself, and the cosine of the (non oriented) angle between two vectors of length one is defined as their dot product. So the equivalence of the two definitions of the dot product is a part of the equivalence of the classical and the modern formulations of ...

  3. Euclidean vector - Wikipedia

    en.wikipedia.org/wiki/Euclidean_vector

    Subtraction of two vectors can be geometrically illustrated as follows: to subtract b from a, place the tails of a and b at the same point, and then draw an arrow from the head of b to the head of a. This new arrow represents the vector (-b) + a, with (-b) being the opposite of b, see drawing. And (-b) + a = a − b. The subtraction of two ...

  4. Hamming distance - Wikipedia

    en.wikipedia.org/wiki/Hamming_distance

    For a fixed length n, the Hamming distance is a metric on the set of the words of length n (also known as a Hamming space), as it fulfills the conditions of non-negativity, symmetry, the Hamming distance of two words is 0 if and only if the two words are identical, and it satisfies the triangle inequality as well: [2] Indeed, if we fix three words a, b and c, then whenever there is a ...

  5. Dyadics - Wikipedia

    en.wikipedia.org/wiki/Dyadics

    When V is Euclidean n-space, we can use the inner product to identify the dual space with V itself, making a dyadic tensor an elementary tensor product of two vectors in Euclidean space. In this sense, the unit dyadic ij is the function from 3-space to itself sending a 1 i + a 2 j + a 3 k to a 2 i, and jj sends this sum to a 2 j.

  6. Distance from a point to a plane - Wikipedia

    en.wikipedia.org/wiki/Distance_from_a_point_to_a...

    The vector equation for a hyperplane in -dimensional Euclidean space through a point with normal vector is () = or = where =. [3] The corresponding Cartesian form is a 1 x 1 + a 2 x 2 + ⋯ + a n x n = d {\displaystyle a_{1}x_{1}+a_{2}x_{2}+\cdots +a_{n}x_{n}=d} where d = p ⋅ a = a 1 p 1 + a 2 p 2 + ⋯ a n p n {\displaystyle d=\mathbf {p ...

  7. Cross product - Wikipedia

    en.wikipedia.org/wiki/Cross_product

    In general, if a vector [a 1, a 2, a 3] is represented as the quaternion a 1 i + a 2 j + a 3 k, the cross product of two vectors can be obtained by taking their product as quaternions and deleting the real part of the result. The real part will be the negative of the dot product of the two vectors.

  8. Matrix multiplication - Wikipedia

    en.wikipedia.org/wiki/Matrix_multiplication

    A; vectors in lowercase bold, e.g. a; and entries of vectors and matrices are italic (they are numbers from a field), e.g. A and a. Index notation is often the clearest way to express definitions, and is used as standard in the literature. The entry in row i, column j of matrix A is indicated by (A) ij, A ij or a ij. In contrast, a single ...

  9. Riemannian manifold - Wikipedia

    en.wikipedia.org/wiki/Riemannian_manifold

    The dot product of two vectors tangent to the sphere sitting inside 3-dimensional Euclidean space contains information about the lengths and angle between the vectors. The dot products on every tangent plane, packaged together into one mathematical object, are a Riemannian metric.