A fast training algorithm for neural networks
Jarosław Bilski, Leszek Rutkowski · IEEE Transactions on Circuits and Systems II Analog and Digital Signal Processing · 1998
The recursive least squares method (RLS) is derived for the learning of multilayer feedforward neural networks. Simulation results on the XOR, 4-2-4 encoder, and function approximation problems indicate a fast learning process in comparison to the classical and momentum backpropagation (BP) algorithms.