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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 5
1381-1386

Research and application of spiking neural network model based on LSTM structure

Wang Qinghua1,2
Wang Lina1,2
Xu Song1,2
1. Beijing Aerospace Automatic Control Institute, Beijing 100854, China
2. National Key Laboratory of Science & Technology on Aerospace Intelligent Control, Beijing 100854, China
DOI: 10.19734/j.issn.1001-3695.2020.05.0123

Abstract

SNN is a novel biologically interpretable network model. In response to the problem that traditional SNN models have inadequate representation ability and cannot apply to practical tasks, this paper studied the capability of SNN to process EEG recognition tasks and developed a SNN model with long short-term memory structure. Firstly, this paper adopted the improved BSA encoding algorithm to process the EEG signals. Secondly, this paper constructed the spiking neuron with an adaptive threshold and established the SNN model with LSTM structure using the PyTorch framework. Finally, this paper utilized the surrogate gradient method to overcome the non-differentiable problem of spike activity and directly trained the SNN based on backpropagation while retaining the dynamic nature of the neuron. Simulation experiments show that the improved BSA is more flexible and reliable. Simultaneously, the SNN model with LSTM structure improves the representation ability and achieves an accuracy that can compete with traditional deep learning model in EEG recognition tasks.

Foundation Support

军队科研资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.05.0123
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 5
Section: Algorithm Research & Explore
Pages: 1381-1386
Serial Number: 1001-3695(2021)05-018-1381-06

Publish History

[2021-05-05] Printed Article

Cite This Article

王清华, 王丽娜, 徐颂. 融合LSTM结构的脉冲神经网络模型研究与应用 [J]. 计算机应用研究, 2021, 38 (5): 1381-1386. (Wang Qinghua, Wang Lina, Xu Song. Research and application of spiking neural network model based on LSTM structure [J]. Application Research of Computers, 2021, 38 (5): 1381-1386. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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