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/external/eigen/blas/
dtpsv.f	13 * DTPSV solves one of the systems of equations 37 * On entry, TRANS specifies the equations to be solved as
stpsv.f	13 * STPSV solves one of the systems of equations 37 * On entry, TRANS specifies the equations to be solved as
ztpsv.f	13 * ZTPSV solves one of the systems of equations 37 * On entry, TRANS specifies the equations to be solved as
level2_impl.h	318 /** DTBSV solves one of the systems of equations 404 /** DTPSV solves one of the systems of equations
/external/ceres-solver/internal/ceres/
implicit_schur_complement.h	57 // The normal equations are given by
schur_eliminator_impl.h	200 // compute the entries of the normal equations and the gradient 205 // to this y block in the normal equations. This computation is 207 // gaussian elimination to the rhs of the normal equations,
corrector_test.cc	144 // equations match the robustified gauss newton approximation.
linear_solver.h	117 // equations. The first elimination group corresponds to the
visibility_based_preconditioner_test.cc	94 // equations better conditioned and makes the tests below better
/external/eigen/test/eigen2/
eigen2_hyperplane.cpp	99 // the line equations should be normalized so that a^2+b^2=1
/external/eigen/test/
geo_hyperplane.cpp	100 // the line equations should be normalized so that a^2+b^2=1
/external/v8/benchmarks/
run.html	121 <li><b>NavierStokes</b><br>Solves NavierStokes equations in 2D, heavily manipulating double precision arrays. Based on Oliver Hunt's code (<i>387 lines</i>).</li>
/external/ceres-solver/docs/
solving.tex	81 An inexact Newton method requires two ingredients. First, a cheap method for approximately solving systems of linear equations. Typically an iterative linear solver like the Conjugate Gradients method is used for this purpose~\cite{nocedal2000numerical}. Second, a termination rule for the iterative solver. A typical termination rule is of the form 223 Let $H(x)= J(x)^\top J(x)$ and $g(x) = -J(x)^\top f(x)$. For notational convenience let us also drop the dependence on $x$. Then it is easy to see that solving~\eqref{eq:simple2} is equivalent to solving the {\em normal equations} 238 Large non-linear least square problems are usually sparse. In such cases, using a dense QR factorization is inefficient. Let $H = R^\top R$ be the Cholesky factorization of the normal equations, where $R$ is an upper triangular matrix, then the solution to ~\eqref{eq:normal} is given by 249 Cholesky factorization of the normal equations. Ceres uses 253 sparse Cholesky factorization of the normal equations. This leads to 323 For general sparse problems, if the problem is too large for \texttt{CHOLMOD} or a sparse linear algebra library is not linked into Ceres, another option is the \texttt{CGNR} solver. This solver uses the Conjugate Gradients solver on the {\em normal equations}, but without forming the normal equations explicitly. It exploits the relation 342 Equation~\eqref{eq:schurtrick1} is closely related to {\em Domain Decomposition methods} for solving large linear systems that arise in structural engineering and partial differential equations. In the language of Domain Decomposition, each point in a bundle adjustment problem is a domain, and the cameras form the interface between these domains. The iterative solution of the Schur complement then falls within the sub-category of techniques known as Iterative Sub-structuring~\cite{saad2003iterative,mathew2008domain}. 395 from the two equations, solving for y and then back substituting     [all...]
ceres-solver.bib	133 Title = {{Domain decomposition methods for the numerical solution of partial differential equations}},
/external/eigen/unsupported/Eigen/src/IterativeSolvers/
GMRES.h	23 * \param mat matrix of linear system of equations 24 * \param Rhs right hand side vector of linear system of equations
/frameworks/av/media/libeffects/lvm/lib/SpectrumAnalyzer/src/
LVPSA_Control.c	446 /* 1. The equations used are as follows: */ 561 /* 1. The equations used are as follows: */     [all...]
/external/skia/include/core/
SkXfermode.h	86 For these equations, the colors are in premultiplied state.
/external/skia/legacy/include/core/
SkXfermode.h	82 For these equations, the colors are in premultiplied state.
/external/eigen/Eigen/src/Eigen2Support/Geometry/
Hyperplane.h	172 // since the line equations ax+by=c are normalized with a^2+b^2=1, the following tests
/external/eigen/Eigen/src/Geometry/
Hyperplane.h	183 // since the line equations ax+by=c are normalized with a^2+b^2=1, the following tests
/external/eigen/doc/
C06_TutorialLinearAlgebra.dox	25 \b The \b problem: You have a system of equations, that you have written as a single matrix equation
/external/libgsm/src/
lpc.c	295 /* This procedure needs four tables; the following equations
/external/ceres-solver/include/ceres/
solver.h	181 // the normal equations J'J is used to control the size of the 274 // from the two equations, solving for y and then back substituting
/external/eigen/Eigen/src/Eigenvalues/
EigenSolver.h	465 else // Solve real equations 527 // Solve complex equations
/external/skia/src/gpu/
GrDrawState.h	266 * there aren't per-vertex edge equations. 297 * there aren't per-vertex edge equations.     [all...]

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