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The Computational Power of Complex-Valued Neuron

Part of the Lecture Notes in Computer Science book series (LNCS,volume 2714)

Abstract

There exist some problems that cannot be solved with conventional usual 2-layered real-valued neural networks (i.e., a single realvalued neuron) such as the XOR problem and the detection of symmetry. In this paper, it will be proved that such problems can be solved by a 2-layered complex-valued neural network (i.e., a single complex-valued neuron) with the orthogonal decision boundaries. Furthermore, it will be shown that the fading equalization problem can be successfully solved by the 2-layered complex-valued neural network with the highest generalization ability.

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  • DOI: 10.1007/3-540-44989-2_118
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References

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© 2003 Springer-Verlag Berlin Heidelberg

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Nitta, T. (2003). The Computational Power of Complex-Valued Neuron. In: Kaynak, O., Alpaydin, E., Oja, E., Xu, L. (eds) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. ICANN ICONIP 2003 2003. Lecture Notes in Computer Science, vol 2714. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44989-2_118

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  • DOI: https://doi.org/10.1007/3-540-44989-2_118

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40408-8

  • Online ISBN: 978-3-540-44989-8

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