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A Novel Neural Network Based on Quantum Computing

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Abstract

Since the first quantum neural network based on quantum computing was proposed by famous scholar Kak, much attention has been taken focus on designing new quantum neural network models. In this paper, a novel efficient quantum feed-forward neural network based on quantum computing is established, which adopts genetic algorithm to improve the traditional back propagation algorithm in parameters learning process. We clearly show the mathematical process of the new proposed quantum network model and improved algorithm. The experimental results of MATLAB simulations show that the new network model which makes the best use of fast quantum neural computation does a better job in function approximation and prediction of educational short video’s spreading capacity than traditional back propagation neural network, and the improved algorithm is more efficient than common back propagation algorithm in the proposed quantum network model. Our model can be widely used in weather prediction, handwriting recognition, speech recognition, and other aspects.

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Authors and Affiliations

  1. Teaching and Research Section of Political, PLA Information Engineering University, Luoyang, 471003, Henan, China

    Bu-Qing Chen

  2. State Key Laboratory of Integrated Service Networks, Xidian University, Xi’an, 710121, Shaanxi, China

    Xu-Feng Niu

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  1. Bu-Qing Chen
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  2. Xu-Feng Niu
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Correspondence to Bu-Qing Chen.

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Chen, BQ., Niu, XF. A Novel Neural Network Based on Quantum Computing. Int J Theor Phys 59, 2029–2043 (2020). https://doi.org/10.1007/s10773-020-04475-4

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  • DOI: https://doi.org/10.1007/s10773-020-04475-4

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