From Zhang Neural Network to scaled hyperpower iterations

A class of scaled hyperpower iterative methods for computing outer inverses is considered. This class appears during the construction of the discrete-time Zhang neural network for computing the usual matrix inverse. The usual hyperpower iterative methods belong to this class. Additionally, a more general class of scaled iterative methods, which includes the scaled hyperpower method, is defined and studied. Different values of the real scaling parameter are investigated both theoretically and numerically.