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

Alfons Josef Schuster, Daniel Berrar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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.

Original languageEnglish
Title of host publicationCommunications in Computer and Information Science
PublisherSpringer Verlag
Pages219-234
Number of pages16
Volume404 CCIS
ISBN (Print)9783642541209
DOIs
Publication statusPublished - 2014
Event1st International Aizu Conference on Biomedical Informatics and Technology, ACBIT 2013 - Aizu-Wakamatsu
Duration: 2013 Sep 162013 Sep 17

Publication series

NameCommunications in Computer and Information Science
Volume404 CCIS
ISSN (Print)18650929

Other

Other1st International Aizu Conference on Biomedical Informatics and Technology, ACBIT 2013
CityAizu-Wakamatsu
Period13/9/1613/9/17

Fingerprint

Neural networks
Neurons
Experiments

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Schuster, A. J., & Berrar, D. (2014). Towards Nature-Inspired Modularization of Artificial Neural Networks via Static and Dynamic Weights. In Communications in Computer and Information Science (Vol. 404 CCIS, pp. 219-234). (Communications in Computer and Information Science; Vol. 404 CCIS). Springer Verlag. https://doi.org/10.1007/978-3-642-54121-6_19

Towards Nature-Inspired Modularization of Artificial Neural Networks via Static and Dynamic Weights. / Schuster, Alfons Josef; Berrar, Daniel.

Communications in Computer and Information Science. Vol. 404 CCIS Springer Verlag, 2014. p. 219-234 (Communications in Computer and Information Science; Vol. 404 CCIS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Schuster, AJ & Berrar, D 2014, Towards Nature-Inspired Modularization of Artificial Neural Networks via Static and Dynamic Weights. in Communications in Computer and Information Science. vol. 404 CCIS, Communications in Computer and Information Science, vol. 404 CCIS, Springer Verlag, pp. 219-234, 1st International Aizu Conference on Biomedical Informatics and Technology, ACBIT 2013, Aizu-Wakamatsu, 13/9/16. https://doi.org/10.1007/978-3-642-54121-6_19
Schuster AJ, Berrar D. Towards Nature-Inspired Modularization of Artificial Neural Networks via Static and Dynamic Weights. In Communications in Computer and Information Science. Vol. 404 CCIS. Springer Verlag. 2014. p. 219-234. (Communications in Computer and Information Science). https://doi.org/10.1007/978-3-642-54121-6_19
Schuster, Alfons Josef ; Berrar, Daniel. / Towards Nature-Inspired Modularization of Artificial Neural Networks via Static and Dynamic Weights. Communications in Computer and Information Science. Vol. 404 CCIS Springer Verlag, 2014. pp. 219-234 (Communications in Computer and Information Science).
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