A spike trains encoding and decoding solution for the spiking neural networks

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Authors

  • Nguyen Van Tuan (Corresponding Author) Institute of Missile and Control Engineering, Le Quy Don Technical University
  • Truong Dang Khoa Institute of Missile and Control Engineering, Le Quy Don Technical University
  • Pham Trung Dung Institute of Missile and Control Engineering, Le Quy Don Technical University
  • Dinh Huu Tai Fundamental Technique Faculty, Air Force Air Defense Academy

DOI:

https://doi.org/10.54939/1859-1043.j.mst.91.2023.28-34

Keywords:

Spike encoding; Spike decoding; Spiking neural network; Latency encoding.

Abstract

This paper proposes a spike train encoding and decoding solution to process input and output signals for the spiking neural networks. The efficiency of the proposed solution is verified by the experimental tasks: The XOR classification problem and the aerodynamic coefficients identification of an aircraft from the data sets are recorded from flights. The results show that the proposed encoding and decoding solution has a higher convergence rate to the set values, and the mean squared error smaller than another solution is introduced in this research.

References

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Published

25-11-2023

How to Cite

Nguyen Van Tuan, Truong Dang Khoa, Pham Trung Dung, and Dinh Huu Tai. “A Spike Trains Encoding and Decoding Solution for the Spiking Neural Networks”. Journal of Military Science and Technology, vol. 91, no. 91, Nov. 2023, pp. 28-34, doi:10.54939/1859-1043.j.mst.91.2023.28-34.

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