Learning Temporal Sequences by Complex Neurons with Local Feedback

Abstract

To deal with temporal sequences is very important and difficult problem for applications of neural networks. In this paper, we propose a Multilayer Network using Complex neurons with local Feedback (MNCF). A complex neuron can keep previous information more easily than a real neuron because of the phase component. We derive simple learning algorithm based on the back-propagation for temporal sequences. It can be considered as a generalized original back-propagation. It is shown in computer simulations that the proposed network has better ability than the conventional real ones, including Elman's network.