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  2. Distance from a point to a plane - Wikipedia

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

    Now the problem has become one of finding the nearest point on this plane to the origin, and its distance from the origin. The point on the plane in terms of the original coordinates can be found from this point using the above relationships between and , between and , and between and ; the distance in terms of the original coordinates is the ...

  3. Distance from a point to a line - Wikipedia

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

    The distance (or perpendicular distance) from a point to a line is the shortest distance from a fixed point to any point on a fixed infinite line in Euclidean geometry. It is the length of the line segment which joins the point to the line and is perpendicular to the line. The formula for calculating it can be derived and expressed in several ways.

  4. Hyperplane - Wikipedia

    en.wikipedia.org/wiki/Hyperplane

    In geometry, a hyperplane of an n-dimensional space V is a subspace of dimension n − 1, or equivalently, of codimension 1 in V.The space V may be a Euclidean space or more generally an affine space, or a vector space or a projective space, and the notion of hyperplane varies correspondingly since the definition of subspace differs in these settings; in all cases however, any hyperplane can ...

  5. Hesse normal form - Wikipedia

    en.wikipedia.org/wiki/Hesse_normal_form

    Distance from the origin O to the line E calculated with the Hesse normal form. Normal vector in red, line in green, point O shown in blue. In analytic geometry, the Hesse normal form (named after Otto Hesse) is an equation used to describe a line in the Euclidean plane, a plane in Euclidean space, or a hyperplane in higher dimensions.

  6. Chebyshev distance - Wikipedia

    en.wikipedia.org/wiki/Chebyshev_distance

    In mathematics, Chebyshev distance (or Tchebychev distance), maximum metric, or L ∞ metric [1] is a metric defined on a real coordinate space where the distance between two points is the greatest of their differences along any coordinate dimension. [2] It is named after Pafnuty Chebyshev.

  7. Support function - Wikipedia

    en.wikipedia.org/wiki/Support_function

    of this half space. The hyperplane H(x) is therefore called a supporting hyperplane with exterior (or outer) unit normal vector x. The word exterior is important here, as the orientation of x plays a role, the set H(x) is in general different from H(−x). Now h A (x) is the (signed) distance of H(x) from the origin.

  8. Duality (projective geometry) - Wikipedia

    en.wikipedia.org/wiki/Duality_(projective_geometry)

    Similarly, a hyperplane H is an absolute hyperplane (self-conjugate hyperplane) if H ⊥ I H. Expressed in other terms, a point x is an absolute point of polarity π with associated sesquilinear form φ if φ(x, x) = 0 and if φ is written in terms of matrix G, x T G x σ = 0. The set of absolute points of each type of polarity can be described.

  9. Signed distance function - Wikipedia

    en.wikipedia.org/wiki/Signed_distance_function

    The graph (bottom, in red) of the signed distance between the points on the xy plane (in blue) and a fixed disk (also represented on top, in gray) A more complicated set (top) and the graph of its signed distance function (bottom, in red).