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Some formulas in the documentation

release/4.3a0
Frank Dellaert 2012-01-22 00:09:38 +00:00
parent ddbce44800
commit b0dea340d2
1 changed files with 4 additions and 4 deletions
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8
gtsam/linear/GaussianConditional.h
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@ -43,7 +43,7 @@ class JacobianFactor;
/**
* A conditional Gaussian functions as the node in a Bayes network
* It has a set of parents y,z, etc. and implements a probability density on x.
* The negative log-probability is given by || Rx - (d - Sy - Tz - ...)||^2
* The negative log-probability is given by \f$ |Rx - (d - Sy - Tz - ...)|^2 \f$
*/
class GaussianConditional : public IndexConditional {
@ -65,7 +65,7 @@ public:
protected:
/** Store the conditional as one big upper-triangular wide matrix, arranged
* as [ R S1 S2 ... d ]. Access these blocks using a VerticalBlockView.
* as \f$ [ R S1 S2 ... d ] \f$. Access these blocks using a VerticalBlockView.
*
* WARNING!!! When using with LDL, R is the permuted upper triangular matrix.
* Its columns/rows do not correspond to the correct components of the variables.
@ -110,7 +110,7 @@ public:
/**
* constructor with number of arbitrary parents (only used in unit tests,
* std::list is not efficient)
* |Rx+sum(Ai*xi)-d|
* \f$ |Rx+sum(Ai*xi)-d| \f$
*/
GaussianConditional(Index key, const Vector& d,
const Matrix& R, const std::list<std::pair<Index, Matrix> >& parents, const Vector& sigmas);
@ -199,7 +199,7 @@ public:
* assuming that parents have been solved already.
*
* @param x values structure with solved parents, and the RHS for this conditional
* @return solution x = R \ (d - Sy - Tz - ...) for each frontal variable
* @return solution \f$ x = R \ (d - Sy - Tz - ...) \f$ for each frontal variable
*/
void solveInPlace(VectorValues& x) const;