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Math module: LevenbergMarquardt.h: Rm the confusion between model and…

… const function
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commit 76eaceda9c7a65c0b5d78e1e718b615b3da97a51 1 parent f9b7a0e
@oleg-alexandrov oleg-alexandrov authored
Showing with 3 additions and 3 deletions.
  1. +3 −3 src/vw/Math/LevenbergMarquardt.h
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6 src/vw/Math/LevenbergMarquardt.h
@@ -64,7 +64,7 @@ namespace math {
/// * Defines a jacobian_type corresponding to the space of
/// jacobian matrices. Typically Matrix<foo>.
/// * Defines a method: result_type operator()( domain_type const& x ) const;
- /// that evaluates the cost function at the given point.
+ /// that evaluates the model function at the given point.
/// * The domain_type must implement a method: domain_type domain_type::operator+( gradient_type const& g ) const;
/// that adds a tangent vector to a position. You get this for
/// free if both domain_type and gradient_type are Vector<foo>.
@@ -80,7 +80,7 @@ namespace math {
/// In addition, depending on the application, you may want to also define:
///
/// * Defines a method: jacobian_type jacobian( domain_type const& x ) const;
- /// that evaluates the jacobian of the cost function at the
+ /// that evaluates the jacobian of the model function at the
/// given point. This will override the default implementation in this base
/// class which computes the derivatives numerically.
///
@@ -153,7 +153,7 @@ namespace math {
/// That is, a least squares problem where the objective is to find a
/// parameter vector x such that the model function h(x), evaluates
/// as closely as possible to the observations z in a least squares
- /// sense.
+ /// sense, that is, the cost function J(p) is minimized.
///
/// Requires:
/// - a seed parameter vector x
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