DocumentCode :
3254601
Title :
Learning temporal sequences by complex neurons with local feedback
Author :
Kinouchi, Makoto ; Hagiwara, Masafumi
Author_Institution :
Dept. of Electr. Eng., Keio Univ., Yokohama, Japan
Volume :
6
fYear :
1995
fDate :
Nov/Dec 1995
Firstpage :
3165
Abstract :
To deal with temporal sequences is a very important and difficult problem for application of neural networks. We propose a multilayer network using complex neurons with local feedback (MNCF). A complex neuron can keep previous information by using the phase component. We derive a simple learning algorithm based on backpropagation for temporal sequences. It is shown in computer simulations that the proposed network has better ability than conventional real ones, including Elman´s network
Keywords :
backpropagation; feedback; multilayer perceptrons; temporal logic; MNCF; backpropagation; complex neurons; computer simulations; local feedback; multilayer network; neural networks; phase component; previous information; simple learning algorithm; temporal sequence learning; Application software; Computer simulation; Delay effects; Feedforward neural networks; Multi-layer neural network; Neural networks; Neurofeedback; Neurons; Nonhomogeneous media; Output feedback;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location :
Perth, WA
Print_ISBN :
0-7803-2768-3
Type :
conf
DOI :
10.1109/ICNN.1995.487291
Filename :
487291
Link To Document :
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