HomeSort by relevance Sort by last modified time
    Searched refs:squared (Results 1 - 4 of 4) sorted by null

  /external/libvpx/libvpx/vp8/common/x86/
postproc_sse2.asm 559 pmaddwd xmm1, xmm2 ; squared of 7+-8 8+-7 9+-6 10+-5
570 pshufd xmm3, xmm1, 3 ; 0000 8--7 8--7 8--7 squared
571 pshufd xmm4, xmm2, 3 ; 0000 8--7 8--7 8--7 squared
576 pshufd xmm3, xmm1, 01011111b ; 0000 0000 9--6 9--6 squared
577 pshufd xmm4, xmm2, 01011111b ; 0000 0000 9--6 9--6 squared
582 pshufd xmm3, xmm1, 10111111b ; 0000 0000 8--7 8--7 squared
583 pshufd xmm4, xmm2, 10111111b ; 0000 0000 8--7 8--7 squared
  /external/bouncycastle/bcprov/src/main/java/org/bouncycastle/math/ec/
ECFieldElement.java 1033 IntArray squared = x.square(m); local
    [all...]
  /external/ceres-solver/docs/
bundleadjustment.tex 6 Given a set of measured image feature locations and correspondences, the goal of bundle adjustment is to find 3D point positions and camera parameters that minimize the reprojection error. This optimization problem is usually formulated as a non-linear least squares problem, where the error is the squared $L_2$ norm of the difference between the observed feature location and the projection of the corresponding 3D point on the image plane of the camera. Ceres has extensive support for solving bundle adjustment problems.
84 NULL /* squared loss */,
modeling.tex 227 so that they mimic the squared cost for small residuals.
242 The reason for the appearance of squaring is that $a$ is in the units of the residual vector norm whereas $s$ is a squared norm. For applications it is more convenient to specify $a$ than
437 \texttt{NULL}, in which case the cost of the term is just the squared norm

Completed in 129 milliseconds