Abstract
The learning process of multi-layered neural networks and their fast learning algorithm are presented in this paper. The ability of hidden units was tested in a learning of the high order nonlinear functions. The number of hidden units was also optimized in the learning.
The pseudo impedance method was proposed for a fast learning algorithm by analogy of a mechanical impedance control. In pseudo impedance method, learning parameters are determined by the neural network's virtual mass, damping coefficient and stiffness. The usefulness of this metod was verified by comparison with the error back propagation method.
