Documentation bug fixes. Thanks Vladimir Chalupecky Change-Id: I52a11d75adbf7adb1233c4d5ec2bc599448ab240
diff --git a/docs/modeling.tex b/docs/modeling.tex index 82080b7..e6dce1f 100644 --- a/docs/modeling.tex +++ b/docs/modeling.tex
@@ -2,10 +2,12 @@ \chapter{Modeling} \label{chapter:api} \section{\texttt{CostFunction}} -Given parameter blocks $\left[x_{i_1}, \hdots , x_{i_k}\right]$, a \texttt{CostFunction} is responsible for computing -a vector of residuals and if asked a vector of Jacobian matrices, i.e., given $\left[x_{i_1}, \hdots , x_{i_k}\right]$, compute the vector $f_i\left(x_{i_1},\hdots,x_{k_i}\right)$ and the matrices +Given parameter blocks $\left[x_{i_1}, \hdots , x_{i_k}\right]$, a +\texttt{CostFunction} is responsible for computing +a vector of residuals and if asked a vector of Jacobian matrices, i.e., given $\left[x_{i_1}, \hdots , x_{i_k}\right]$, compute the vector $f_i\left(x_{i_1},\hdots,x_{i_k}\right)$ and the matrices + \begin{equation} -J_{ij} = \frac{\partial}{\partial x_{i_j}}f_i\left(x_{i_1},\hdots,x_{k_i}\right),\quad \forall j = i_1,\hdots, i_k +J_{ij} = \frac{\partial}{\partial x_{j}}f_i\left(x_{i_1},\hdots,x_{i_k}\right),\quad \forall j \in \{i_1,\hdots, i_k\} \end{equation} \begin{minted}{c++} class CostFunction { @@ -90,8 +92,8 @@ MyScalarCostFunction(double k): k_(k) {} template <typename T> bool operator()(const T* const x , const T* const y, T* e) const { - e[0] = T(k_) - x[0] * y[0] + x[1] * y[1] - return true; + e[0] = T(k_) - x[0] * y[0] - x[1] * y[1]; + return true; } private: @@ -265,12 +267,12 @@ Then, the robustified gradient and the Gauss-Newton Hessian are \begin{align} g(x) &= \rho'J^\top(x)f(x)\\ - H(x) &= J^\top(x)\left(\rho' + 2 \rho''f(x)f^\top(x)\right)J(x) + H(x) &= J^\top(x)\left(\rho' + 2 \rho''f(x)f^\top(x)\right)J(x) \end{align} -where the terms involving the second derivatives of $f(x)$ have been ignored. Note that $H(x)$ is indefinite if $\rho''f(x)^\top f(x) + \frac{1}{2}\rho' < 0$. If this is not the case, then its possible to re-weight the residual and the Jacobian matrix such that the corresponding linear least squares problem for the robustified Gauss-Newton step. +where the terms involving the second derivatives of $f(x)$ have been ignored. Note that $H(x)$ is indefinite if $\rho''f(x)^\top f(x) + \frac{1}{2}\rho' < 0$. If this is not the case, then its possible to re-weight the residual and the Jacobian matrix such that the corresponding linear least squares problem for the robustified Gauss-Newton step. -Let $\alpha$ be a root of +Let $\alpha$ be a root of \begin{equation} \frac{1}{2}\alpha^2 - \alpha - \frac{\rho''}{\rho'}\|f(x)\|^2 = 0. \end{equation}