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Quantum Classification Algorithm Based on Competitive Learning Neural Network and Entanglement Measure

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Center for Photonics and Smart Materials (CPSM), Zewail City of Science and Technology, October Gardens, 6th of October City, Giza 12578, Egypt
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University of Science and Technology, Zewail City of Science and Technology, October Gardens, 6th of October City, Giza 12578, Egypt
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Department of Physics, College of Sciences, University of Bisha, Bisha 61922, P.O. Box 344, Saudi Arabia
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Physics Department, Faculty of Science, Al-Azhar University, Assiut 71524, Egypt
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Department of Nuclear and Radiation Engineering, Faculty of Engineering, Alexandria University, Alexandria 21544, Egypt
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Deanship of Research and Graduate Studies, Applied Science University, P.O. Box 5055, 55222 Manama, Kingdom of Bahrain
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Institute for Quantum Science and Engineering, Texas A&M University, College Station, TX 77843, USA
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Department of Applied Sciences and Mathematics, College of Arts and Sciences, Abu Dhabi University, 59911 Abu Dhabi, United Arab Emirates
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Department of Mathmatics, Sohage University, Sohag 82524, Egypt
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Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(7), 1277; https://doi.org/10.3390/app9071277
Received: 21 December 2018 / Revised: 17 March 2019 / Accepted: 19 March 2019 / Published: 27 March 2019
(This article belongs to the Special Issue (Quantum) Physical Informatics)
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Abstract

In this paper, we develop a novel classification algorithm that is based on the integration between competitive learning and the computational power of quantum computing. The proposed algorithm classifies an input into one of two binary classes even if the input pattern is incomplete. We use the entanglement measure after applying unitary operators to conduct the competition between neurons in order to find the winning class based on wining-take-all. The novelty of the proposed algorithm is shown in its application to the quantum computer. Our idea is validated via classifying the state of Reactor Coolant Pump of a Risky Nuclear Power Plant and compared with other quantum-based competitive neural networks model. View Full-Text
Keywords: quantum classification models; quantum neural netweorks; competitive Learnings quantum classification models; quantum neural netweorks; competitive Learnings
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Zidan, M.; Abdel-Aty, A.-H.; El-shafei, M.; Feraig, M.; Al-Sbou, Y.; Eleuch, H.; Abdel-Aty, M. Quantum Classification Algorithm Based on Competitive Learning Neural Network and Entanglement Measure. Appl. Sci. 2019, 9, 1277.

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