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Polynomial Clusterons Exhibit Statistical Estimation Abilities

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Neural Nets WIRN Vietri-99

Part of the book series: Perspectives in Neural Computing ((PERSPECT.NEURAL))

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Abstract

The aim of this paper is to investigate the behavior of neural clusterons that learn in an unsupervised fashion by means of an information-theoretic based rule. Particularly the aim is to investigate on the clusteron’s statistical estimation abilities that naturally emerge from their learning behaviors.

This research was financially supported by the Italian MURST.

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Author information

Authors and Affiliations

  1. Dipartimento di Ingegneria Industriale, Univesità di Perugia, Perugia, Italy

    Simone Fiori & Pietro Burrascano

Authors
  1. Simone Fiori
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  2. Pietro Burrascano
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Editor information

Editors and Affiliations

  1. Dipartimento di Scienze Fisiche, “E.R. Caianiello”, Universita di Salerno, 84081, Baronissi (SA), Italy

    Maria Marinaro

  2. DMI, Universita di Salerno, 84081, Baronissi (SA), Italy

    Roberto Tagliaferri

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© 1999 Springer-Verlag London Limited

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Fiori, S., Burrascano, P. (1999). Polynomial Clusterons Exhibit Statistical Estimation Abilities. In: Marinaro, M., Tagliaferri, R. (eds) Neural Nets WIRN Vietri-99. Perspectives in Neural Computing. Springer, London. https://doi.org/10.1007/978-1-4471-0877-1_7

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  • DOI: https://doi.org/10.1007/978-1-4471-0877-1_7

  • Publisher Name: Springer, London

  • Print ISBN: 978-1-4471-1226-6

  • Online ISBN: 978-1-4471-0877-1

  • eBook Packages: Springer Book Archive

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