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Diffstat (limited to 'help/en_US/lsqnonneg.xml')
| -rw-r--r-- | help/en_US/lsqnonneg.xml | 18 |
1 files changed, 9 insertions, 9 deletions
diff --git a/help/en_US/lsqnonneg.xml b/help/en_US/lsqnonneg.xml index daf79bf..662ba2a 100644 --- a/help/en_US/lsqnonneg.xml +++ b/help/en_US/lsqnonneg.xml @@ -35,21 +35,21 @@ <title>Parameters</title> <variablelist> <varlistentry><term>C :</term> - <listitem><para> a matrix of doubles, represents the multiplier of the solution x in the expression C*x - d. C is M-by-N, where M is the number of equations, and N is the number of elements of x.</para></listitem></varlistentry> + <listitem><para> a matrix of double, represents the multiplier of the solution x in the expression C*x - d. Number of columns in C is equal to the number of elements in x.</para></listitem></varlistentry> <varlistentry><term>d :</term> - <listitem><para> a vector of doubles, represents the additive constant term in the expression C*x - d. d is M-by-1, where M is the number of equations.</para></listitem></varlistentry> + <listitem><para> a vector of double, represents the additive constant term in the expression C*x - d. Number of elements in d is equal to the number of rows in C matrix.</para></listitem></varlistentry> <varlistentry><term>xopt :</term> - <listitem><para> a vector of doubles, the computed solution of the optimization problem.</para></listitem></varlistentry> + <listitem><para> a vector of double, the computed solution of the optimization problem.</para></listitem></varlistentry> <varlistentry><term>resnorm :</term> <listitem><para> a double, objective value returned as the scalar value norm(C*x-d)^2.</para></listitem></varlistentry> <varlistentry><term>residual :</term> - <listitem><para> a vector of doubles, solution residuals returned as the vector C*x-d.</para></listitem></varlistentry> + <listitem><para> a vector of double, solution residuals returned as the vector C*x-d.</para></listitem></varlistentry> <varlistentry><term>exitflag :</term> - <listitem><para> Integer identifying the reason the algorithm terminated.</para></listitem></varlistentry> + <listitem><para> Integer identifying the reason the algorithm terminated. It could be 0, 1 or 2 i.e. Optimal, Maximum Number of Iterations Exceeded, CPU time exceeded.</para></listitem></varlistentry> <varlistentry><term>output :</term> - <listitem><para> Structure containing information about the optimization. Right now it contains number of iteration.</para></listitem></varlistentry> + <listitem><para> Structure containing information about the optimization. This version only contains number of iterations.</para></listitem></varlistentry> <varlistentry><term>lambda :</term> - <listitem><para> Structure containing the Lagrange multipliers at the solution x (separated by constraint type).It contains lower, upper and linear equality, inequality constraints.</para></listitem></varlistentry> + <listitem><para> Structure containing the Lagrange multipliers at the solution x. It contains lower and upper bound multiplier.</para></listitem></varlistentry> </variablelist> </refsection> @@ -62,13 +62,13 @@ Solves nonnegative least-squares curve fitting problems specified by : <latex> \begin{eqnarray} &\mbox{min}_{x} -& 1/2||C*x - d||_2^2 \\ +& 1/2||C⋅x - d||_2^2 \\ & & x \geq 0 \\ \end{eqnarray} </latex> </para> <para> -We are calling IPOpt for solving the nonnegative least-squares curve fitting problems, IPOpt is a library written in C++. +The routine calls Ipopt for solving the nonnegative least-squares curve fitting problems, Ipopt is a library written in C++. </para> <para> </para> |