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  2. Dot product - Wikipedia

    en.wikipedia.org/wiki/Dot_product

    Illustration showing how to find the angle between vectors using the dot product Calculating bond angles of a symmetrical tetrahedral molecular geometry using a dot product. In Euclidean space, a Euclidean vector is a geometric object that possesses both a magnitude and a direction. A vector can be pictured as an arrow.

  3. Direction cosine - Wikipedia

    en.wikipedia.org/wiki/Direction_cosine

    If vectors u and v have direction cosines (α u, β u, γ u) and (α v, β v, γ v) respectively, with an angle θ between them, their units vectors are ^ = + + (+ +) = + + ^ = + + (+ +) = + +. Taking the dot product of these two unit vectors yield, ^ ^ = + + = ⁡, where θ is the angle between the two unit vectors, and is also the angle between u and v.

  4. Cross product - Wikipedia

    en.wikipedia.org/wiki/Cross_product

    The dot product of two unit vectors behaves just oppositely: it is zero when the unit vectors are perpendicular and 1 if the unit vectors are parallel. Unit vectors enable two convenient identities: the dot product of two unit vectors yields the cosine (which may be positive or negative) of the angle between the two unit vectors.

  5. 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.

  6. Cosine similarity - Wikipedia

    en.wikipedia.org/wiki/Cosine_similarity

    The angle between two term frequency vectors cannot be greater than 90°. If the attribute vectors are normalized by subtracting the vector means (e.g., ¯), the measure is called the centered cosine similarity and is equivalent to the Pearson correlation coefficient. For an example of centering,

  7. Metric tensor - Wikipedia

    en.wikipedia.org/wiki/Metric_tensor

    A metric tensor at p is a function g p (X p, Y p) which takes as inputs a pair of tangent vectors X p and Y p at p, and produces as an output a real number , so that the following conditions are satisfied: g p is bilinear. A function of two vector arguments is bilinear if it is linear separately in each argument.

  8. Angle - Wikipedia

    en.wikipedia.org/wiki/Angle

    The angle between two planes (such as two adjacent faces of a polyhedron) is called a dihedral angle. [18] It may be defined as the acute angle between two lines normal to the planes. The angle between a plane and an intersecting straight line is complementary to the angle between the intersecting line and the normal to the plane.

  9. Vector projection - Wikipedia

    en.wikipedia.org/wiki/Vector_projection

    Since the notions of vector length and angle between vectors can be generalized to any n-dimensional inner product space, this is also true for the notions of orthogonal projection of a vector, projection of a vector onto another, and rejection of a vector from another. In some cases, the inner product coincides with the dot product.