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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,
covariance_impl.h 38 #include "ceres/covariance.h"
51 explicit CovarianceImpl(const Covariance::Options& options);
77 Covariance::Options options_;
covariance_test.cc 31 #include "ceres/covariance.h"
96 Covariance::Options options;
285 void ComputeAndCompareCovarianceBlocks(const Covariance::Options& options,
288 // covariance computation is correct.
315 Covariance covariance(options);
316 EXPECT_TRUE(covariance.Compute(covariance_blocks, &problem_));
322 GetCovarianceBlockAndCompare(block1, block2, covariance, expected_covariance);
324 GetCovarianceBlockAndCompare(block2, block1, covariance, expected_covariance);
331 const Covariance& covariance
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covariance_impl.cc 63 #include "ceres/covariance.h"
78 CovarianceImpl::CovarianceImpl(const Covariance::Options& options)
104 << "Covariance::GetCovarianceBlock called before Covariance::Compute";
106 << "Covariance::GetCovarianceBlock called when Covariance::Compute "
110 // covariance block is also zero.
134 // Find where in the covariance matrix the block is located.
146 // covariance block begin.
153 LOG(ERROR) << "Unable to find covariance block for
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  /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
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problem.h 463 friend class Covariance;
  /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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