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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 717))

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Abstract

In this paper we propose an algorithm, Simple Hebbian PCA, and prove that it is able to calculate the principal component analysis (PCA) in a distributed fashion across nodes. It simplifies existing network structures by removing intralayer weights, essentially cutting the number of weights that need to be trained in half.

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Correspondence to Manuel Mazzara .

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Johard, L., Rivera, V., Mazzara, M., Lee, J.Y. (2018). Self-adaptive Node-Based PCA Encodings. In: Ciancarini, P., Litvinov, S., Messina, A., Sillitti, A., Succi, G. (eds) Proceedings of 5th International Conference in Software Engineering for Defence Applications. SEDA 2016. Advances in Intelligent Systems and Computing, vol 717. Springer, Cham. https://doi.org/10.1007/978-3-319-70578-1_1

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  • DOI: https://doi.org/10.1007/978-3-319-70578-1_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-70577-4

  • Online ISBN: 978-3-319-70578-1

  • eBook Packages: EngineeringEngineering (R0)

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