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Quaternion Neural Network and Its Application

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2774))

Abstract

Quaternion neural networks are models of which computations in the neurons is based on quaternions, the four-dimensional equivalents of imaginary numbers. This paper shows by experiments that the quaternion-version of the Back Propagation (BP) algorithm achieves correct geometrical transformations in color space for an image compression problem, whereas real-valued BP algorithms fail.

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References

  1. Arena, P., Fortuna, L., Muscato, G., Xibilia, M.G.: Neural Networks in Multidimensional Domains. Lecture Note in Control and Information Sciences 234 (1998)

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  2. Kusakabe, T., Kouda, N., Isokawa, T., Matsui, N.: A Study of Neural Network Based on Quaternion. In: Proceeding of SICE Annual Conference, pp. 776–779 (2002)

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  4. Cottrell, G.W., Munro, P., Zipser, D.: Image compression by back propagation: An example of extensional propagation. ICS report 8702 (1987)

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© 2003 Springer-Verlag Berlin Heidelberg

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Isokawa, T., Kusakabe, T., Matsui, N., Peper, F. (2003). Quaternion Neural Network and Its Application. In: Palade, V., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2003. Lecture Notes in Computer Science(), vol 2774. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45226-3_44

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  • DOI: https://doi.org/10.1007/978-3-540-45226-3_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40804-8

  • Online ISBN: 978-3-540-45226-3

  • eBook Packages: Springer Book Archive

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