A Fast-Converging Algorithm for Nonlinear Mapping of High-Dimensional Data to a Plane

An iterative algorithm for nonlinear mapping of high-dimensional data is developed. The step size of the descent algorithm is chosen to assure convergence. Steepest descent and Coordinate descent are treated. The algorithm is applied to artificial and real data to demonstrate its excellent convergence properties.