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Weightless Neural Models: An Overview

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Women in Computational Intelligence

Part of the book series: Women in Engineering and Science ((WES))

Abstract

This paper presents an overview of research in Weightless Neural Models. Weightless Neural Networks (WNNs) do not have weighted connections between nodes. They use a different kind of neuron, usually based on RAM memory devices. The weightless (or RAM-based) neural networks are based on variations of the RAM node proposed by Aleksander. Recent works in the literature, such as the quantum weightless neuron, provide a novel perspective to this area. The paper describes classical and quantum weightless models and important recent works found in the literature, pointing out the challenges and future directions in the area.

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Author information

Authors and Affiliations

  1. Centro de Informática, Universidade Federal de Pernambuco, Recife, Brazil

    Teresa B. Ludermir

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  1. Teresa B. Ludermir
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Correspondence to Teresa B. Ludermir .

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Editors and Affiliations

  1. Department of Industrial and Systems Engineering and Department of Computer Science and Software Engineering, Auburn University, Auburn, AL, USA

    Alice E Smith

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Ludermir, T.B. (2022). Weightless Neural Models: An Overview. In: Smith, A.E. (eds) Women in Computational Intelligence. Women in Engineering and Science. Springer, Cham. https://doi.org/10.1007/978-3-030-79092-9_15

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