Soft Computing

, Volume 22, Issue 3, pp 691–705 | Cite as

A quantum-inspired version of the nearest mean classifier

  • Giuseppe SergioliEmail author
  • Enrica Santucci
  • Luca Didaci
  • Jarosław A. Miszczak
  • Roberto Giuntini


We introduce a framework suitable for describing standard classification problems using the mathematical language of quantum states. In particular, we provide a one-to-one correspondence between real objects and pure density operators. This correspondence enables us: (1) to represent the nearest mean classifier (NMC) in terms of quantum objects, (2) to introduce a quantum-inspired version of the NMC called quantum classifier (QC). By comparing the QC with the NMC on different datasets, we show how the first classifier is able to provide additional information that can be beneficial on a classical computer with respect to the second classifier.


Bloch sphere Quantum classifier Non-standard application of quantum formalism 



This work has been partly supported by the project “Computational quantum structures at the service of pattern recognition: modeling uncertainty” (CRP-59872) funded by Regione Autonoma della Sardegna, L.R. 7/2007 (2012) and the FIRB project “Structures and Dynamics of Knowledge and Cognition” (F21J12000140001).

Funding This study was funded by Regione Autonoma della Sardegna, L.R. 7/2007, CRP-59872 (2012).

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.Università di CagliariCagliariItaly
  2. 2.Institute of Theoretical and Applied InformaticsPolish Academy of SciencesGliwicePoland

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