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  2. Dot product - Wikipedia

    en.wikipedia.org/wiki/Dot_product

    In such a presentation, the notions of length and angle are defined by means of the 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 ...

  3. Vector multiplication - Wikipedia

    en.wikipedia.org/wiki/Vector_multiplication

    Cross product – also known as the "vector product", a binary operation on two vectors that results in another vector. The cross product of two vectors in 3-space is defined as the vector perpendicular to the plane determined by the two vectors whose magnitude is the product of the magnitudes of the two vectors and the sine of the angle ...

  4. Outer product - Wikipedia

    en.wikipedia.org/wiki/Outer_product

    The dot product is the trace of the outer product. [5] Unlike the dot product, the outer product is not commutative. Multiplication of a vector by the matrix can be written in terms of the inner product, using the relation () = , .

  5. Triple product - Wikipedia

    en.wikipedia.org/wiki/Triple_product

    The scalar triple product (also called the mixed product, box product, or triple scalar product) is defined as the dot product of one of the vectors with the cross product of the other two. Geometric interpretation

  6. Commutative property - Wikipedia

    en.wikipedia.org/wiki/Commutative_property

    When a commutative operation is written as a binary function = (,), then this function is called a symmetric function, and its graph in three-dimensional space is symmetric across the plane =. For example, if the function f is defined as f ( x , y ) = x + y {\displaystyle f(x,y)=x+y} then f {\displaystyle f} is a symmetric function.

  7. Vector calculus identities - Wikipedia

    en.wikipedia.org/wiki/Vector_calculus_identities

    More generally, for a function of n variables (, …,), also called a scalar field, the gradient is the vector field: = (, …,) = + + where (=,,...,) are mutually orthogonal unit vectors. As the name implies, the gradient is proportional to, and points in the direction of, the function's most rapid (positive) change.

  8. 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.

  9. Lists of vector identities - Wikipedia

    en.wikipedia.org/wiki/Lists_of_vector_identities

    Vector algebra relations — regarding operations on individual vectors such as dot product, cross product, etc. Vector calculus identities — regarding operations on vector fields such as divergence, gradient, curl, etc.