* x^{n+1} = x^{n} + \rho_n \rho_{n-1} (x^{n} - x^{n-1}) +
* \frac{\rho_n}{\lambda_{\max{}}-\lambda_{\min{}}} P^{-1} (b-Ax^n).
* @f]
- * where the parameter $rho_0$ is set to $rho_0 =
+ * where the parameter $\rho_0$ is set to $\rho_0 =
* \frac{\lambda_{\max{}}-\lambda_{\min{}}}{\lambda_{\max{}}+\lambda_{\min{}}}$
* for the maximal eigenvalue $\lambda_{\max{}}$ and updated via $\rho_n =
* \left(2\frac{\lambda_{\max{}}+\lambda_{\min{}}}
* many iterations should be performed. The iterations are started from an
* initial vector that depends on the vector type. For the classes
* dealii::Vector or dealii::LinearAlgebra::distributed::Vector, which have
- * fast element access, it is either a vector with entries `(-5.5, -4.5, -3.5,
+ * fast element access, it is a vector with entries `(-5.5, -4.5, -3.5,
* -2.5, ..., 3.5, 4.5, 5.5)` with appropriate epilogue and adjusted such that
* its mean is always zero, which works well for the Laplacian. This setup is
* stable in parallel in the sense that for a different number of processors