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 by the phase component. We derive simple learning algorithm based on the back-propagation for temporal sequences. It is shown in computer simulations that the proposed network has better ability than the conventional real ones, including Elman's network.
| Original language | English |
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| Pages | 3165-3169 |
| Number of pages | 5 |
| Publication status | Published - 1995 Dec 1 |
| Event | Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust Duration: 1995 Nov 27 → 1995 Dec 1 |
Other
| Other | Proceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) |
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| City | Perth, Aust |
| Period | 95/11/27 → 95/12/1 |
ASJC Scopus subject areas
- Software