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  2. Scaling (geometry) - Wikipedia

    en.wikipedia.org/wiki/Scaling_(geometry)

    Each iteration of the Sierpinski triangle contains triangles related to the next iteration by a scale factor of 1/2. In affine geometry, uniform scaling (or isotropic scaling [1]) is a linear transformation that enlarges (increases) or shrinks (diminishes) objects by a scale factor that is the same in all directions (isotropically).

  3. Scale factor (computer science) - Wikipedia

    en.wikipedia.org/wiki/Scale_factor_(computer...

    A scale factor of 1 ⁄ 10 cannot be used here, because scaling 160 by 1 ⁄ 10 gives 16, which is greater than the greatest value that can be stored in this fixed-point format. However, 1 ⁄ 11 will work as a scale factor, because the maximum scaled value, 160 ⁄ 11 = 14. 54, fits within this range. Given this set:

  4. List of common coordinate transformations - Wikipedia

    en.wikipedia.org/wiki/List_of_common_coordinate...

    Note: solving for ′ returns the resultant angle in the first quadrant (< <). To find , one must refer to the original Cartesian coordinate, determine the quadrant in which lies (for example, (3,−3) [Cartesian] lies in QIV), then use the following to solve for :

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    The AOL.com video experience serves up the best video content from AOL and around the web, curating informative and entertaining snackable videos.

  6. Linear fractional transformation - Wikipedia

    en.wikipedia.org/wiki/Linear_fractional...

    Linear fractional transformations are shown to be conformal maps by consideration of their generators: multiplicative inversion z → 1/z and affine transformations z → az + b. Conformality can be confirmed by showing the generators are all conformal. The translation z → z + b is a change of origin and makes no difference to angle.

  7. Renormalization group - Wikipedia

    en.wikipedia.org/wiki/Renormalization_group

    The idea of scale transformations and scale invariance is old in physics: Scaling arguments were commonplace for the Pythagorean school, Euclid, and up to Galileo. [1] They became popular again at the end of the 19th century, perhaps the first example being the idea of enhanced viscosity of Osborne Reynolds, as a way to explain turbulence.

  8. Conformal linear transformation - Wikipedia

    en.wikipedia.org/.../Conformal_linear_transformation

    Conformal linear transformations come in two types, proper transformations preserve the orientation of the space whereas improper transformations reverse it. As linear transformations, conformal linear transformations are representable by matrices once the vector space has been given a basis , composing with each-other and transforming vectors ...

  9. Shear mapping - Wikipedia

    en.wikipedia.org/wiki/Shear_mapping

    the eigenspace of S (associated with the eigenvalue 1) has n − 1 dimensions. S is defective; S is asymmetric; S may be made into a block matrix by at most 1 column interchange and 1 row interchange operation; the area, volume, or any higher order interior capacity of a polytope is invariant under the shear transformation of the polytope's ...

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