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

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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. © Springer-Verlag Berlin Heidelberg 2014.

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Schuster, A., & 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). Springer Verlag. https://doi.org/10.1007/978-3-642-54121-6_19

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