Multi-Valued Neuron with Sigmoid Activation Function for Pattern Classification

DOI: 10.4236/jcc.2014.24023   PDF   HTML     3,423 Downloads   4,733 Views   Citations


Multi-Valued Neuron (MVN) was proposed for pattern classification. It operates with complex-valued inputs, outputs, and weights, and its learning algorithm is based on error-correcting rule. The activation function of MVN is not differentiable. Therefore, we can not apply backpropagation when constructing multilayer structures. In this paper, we propose a new neuron model, MVN-sig, to simulate the mechanism of MVN with differentiable activation function. We expect MVN-sig to achieve higher performance than MVN. We run several classification benchmark datasets to compare the performance of MVN-sig with that of MVN. The experimental results show a good potential to develop a multilayer networks based on MVN-sig.

Share and Cite:

Wu, S. , Chiou, Y. and Lee, S. (2014) Multi-Valued Neuron with Sigmoid Activation Function for Pattern Classification. Journal of Computer and Communications, 2, 172-181. doi: 10.4236/jcc.2014.24023.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Aizenberg, N.N. and Aizenberg, I.N. (1992) CNN Based on Multivalued Neuron as a Model of Associative Memory For Grey Scale Images. In Proceedings of Second IEEE International Workshop on Cellular Neural Networks and their Applications (CNNA-92), 36-41.
[2] Aizenberg, I., Aizenberg, N.N. and Vandewalle, J.P. (2000) Multi-Valued and Universal Binary Neurons: Theory, Learning and Applications. Springer.
[3] Aizenberg, I. and Moraga, C. (2007) Multi-layer Feed Forward Neural Network Based on Multi-Valued Neurons (mlmvn) and a Backpropagation Learning Algo-rithm. Soft Computing—A Fusion of Foundations, Methodologies and Applications, 11, 169-183.
[4] Aizenberg, I., Paliy, D.V., Zurada, J.M. and Astola, J. T. (2008) Blur Identification by Multilayer Neural Network Based on Multivalued Neurons. 19, 883-898.
[5] Aizenberg, I. (2010) Periodic Activation Function and a Modified Learning Algorithm for the Multivalued Neuron. 21, 1939-1949.
[6] Aizenberg, I. (2011) Complex-Valued Neural Networks with Multi-Valued Neurons. Springer.
[7] Wilson, E. (1994) Backpropagation Learning for Systems with Discrete-Valued Functions. Proceedings of the World Congress on Neural Networks, San Diego, California, June.
[8] Hagan, M.T., Demuth, H.B., Beale, M.H., et al. (1996) Neural Network Design. Thomson Learning Stamford, CT.
[9] UCI Machine Learning Repository.

comments powered by Disqus

Copyright © 2020 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.