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  /external/ceres-solver/internal/ceres/
covariance.cc 31 #include "ceres/covariance.h"
41 Covariance::Covariance(const Covariance::Options& options) {
45 Covariance::~Covariance() {
48 bool Covariance::Compute(
54 bool Covariance::GetCovarianceBlock(const double* parameter_block1,
  /external/ceres-solver/include/ceres/
covariance.h 56 // This class allows the user to evaluate the covariance for a
63 // non-linear least squares solve is to analyze the covariance of the
71 // independent variable x with mean f(x) and identity covariance. Then
77 // And the covariance of x* is given by
84 // If J(x*) is rank deficient, then the covariance matrix C(x*) is
89 // Note that in the above, we assumed that the covariance
95 // Where S is a positive semi-definite matrix denoting the covariance
100 // and the corresponding covariance estimate of x* is given by
105 // covariance matrix not equal to identity, then it is the user's
109 // is the inverse square root of the covariance matrix S
    [all...]
  /frameworks/native/services/sensorservice/
Fusion.cpp 131 class Covariance {
136 Covariance() : mSumXX(0.0f), mSumX(0.0f), mN(0) { }
194 // process noise covariance matrix: G.Q.Gt, with
220 // initial covariance: Var{ x(t0) }

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