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Towards Nature-Inspired Modularization of Artificial Neural Networks via Static and Dynamic Weights

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Biomedical Informatics and Technology (ACBIT 2013)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 404))

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Abstract

Many conventional artificial neural network (ANN) models are designed for one application domain only. The work presented in this paper describes ANN models that operate with a higher economy by sharing neurons across domains. The use of two different types of weights—static weights and dynamic weights—is a fundamental feature of the presented models. Results from a comprehensive series of experiments provide evidence for the meaningfulness of the proposed models.

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Author information

Authors and Affiliations

  1. School of International Liberal Studies, Waseda University, Tokyo, Japan

    Alfons Schuster

  2. Tokyo Institute of Technology, Yokohama, Japan

    Daniel Berrar

Authors
  1. Alfons Schuster
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  2. Daniel Berrar
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Editor information

Editors and Affiliations

  1. Aizu Research Cluster for Medical Engineering and Informatics Research Center for Advanced Information Science and Technology, The University of Aizu, 965-8580, Aizuwakamatsu, Fukushima, Japan

    Tuan D. Pham

  2. Department of Cancer Biology, Division of Mathematical Oncology, The Institute of Medical Science, The University of Tokyo, 108-8639, Tokyo, Japan

    Kazuhisha Ichikawa

  3. Chaos Technology Research Lab, 5-26-5 Seta, 520-2134, Otsu-shi, Oyama-Higa, Japan

    Mayumi Oyama-Higa

  4. Department of Biostatistics and Medical Informatics, Faculty of Medicine and Pharmacy, The Free University of Brussels, 103, 1090, Laarbeeklaan, Brussels, Belgium

    Danny Coomans

  5. Department of Computer Science, University of Muenster, Einsteinstrasse 62, 48149, Muenster, Germany

    Xiaoyi Jiang

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© 2014 Springer-Verlag Berlin Heidelberg

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Schuster, A., Berrar, D. (2014). Towards Nature-Inspired Modularization of Artificial Neural Networks via Static and Dynamic Weights. In: Pham, T.D., Ichikawa, K., Oyama-Higa, M., Coomans, D., Jiang, X. (eds) Biomedical Informatics and Technology. ACBIT 2013. Communications in Computer and Information Science, vol 404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54121-6_19

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  • DOI: https://doi.org/10.1007/978-3-642-54121-6_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-54120-9

  • Online ISBN: 978-3-642-54121-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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