Clustering Algorithm of Quantum Self-Organization Network Based on Bloch Spherical Rotation

Authors

Shuyun Yang, 1. Northeast Petroleum University, Daqing 163318, China;;
Panchi Li, 2. School of Computer & Information Technology, Northeast Petroleum University, Daqing 163318, China;

Abstract

Abstract: To enhance the clustering ability of self-origanization network, a quantum-inspired self-organization clustering algorithm was proposed based on Bloch spherical rotation. The clustering samples were mapped to the qubits on the Bloch sphere by taking all the sample values as the phases of the qubits, and the all weight values in the competitive layer were mapped to the qubits randomly distributed on the Bloch sphere. Then, the winning node was obtained by computing the spherical distance between sample and weight value, and the weight values of the winning nodes and its neighborhood were updated by rotating them to the sample on the Bloch sphere until the convergence. The obvious advantage of this method is that it has higher clustering accuracy. The clustering results of the benchmark IRIS sample show that the proposed approach is obviously superior to the classical self-organization network and the K-mean clustering algorithm.

Recommended Citation

Yang, Shuyun and Li, Panchi (2020) "Clustering Algorithm of Quantum Self-Organization Network Based on Bloch Spherical Rotation," Journal of System Simulation: Vol. 27: Iss. 5, Article 26.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss5/26

First Page

1105

Revised Date

2014-07-20

DOI Link

https://doi.org/

Last Page

1111

CLC

TP183

Recommended Citation

Yang Shuyun, Li Panchi. Clustering Algorithm of Quantum Self-Organization Network Based on Bloch Spherical Rotation[J]. Journal of System Simulation, 2015, 27(5): 1105-1111.