Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 3
671-675,688

Brain-inspired class incremental learning

Wang Wei1a
Zhang Zhiying1b
Guo Jielong2
Lan Hai2
Yu Hui2
Wei Xian2
1. a. Foundation Dept. , b. School of Electronics & Information Engineering, Liaoning Technical University, Huludao Liaoning 125105, China
2. Fujian Institute of Material Structure, Chinese Academy of Sciences, Fuzhou 350002, China
DOI: 10.19734/j.issn.1001-3695.2022.06.0359

Abstract

Most existing class incremental learning methods employ data storage or extended network structures, but they cannot effectively alleviate the catastrophic forgetting problem due to memory resource limitation. To solve this issue, this paper proposed a brain-inspired generative replay approach. Firstly, it used VAE-ACGAN to simulate the memory self-organizing system to improve the quality of the generated pseudo-samples. Then, it used a shared parameter module and a private parameter module to protect the extracted features. Finally, the potential variables in the generator used a Gaussian mixture model to select specific replay pseudo-samples. The experimental results of the proposed method on MNIST, Permuted MNIST and CIFAR-10 show that the classification accuracy of the proposed method is 92.91%, 91.44% and 40.58%, respectively, which is significantly better than other class incremental learning methods. Furthermore, the backward transfer and forward transfer metrics reach 3.32% and 0.83% on the MNIST dataset, demonstrating that the model achieves a trade-off between task stability and plasticity, effectively preventing catastrophic forgetting.

Foundation Support

国家自然科学基金青年基金资助项目(61701211)
辽宁省教育厅基本科研项目(LJKZ0362)
福建省科技计划资助项目(2021T3003,2021T3068)
泉州市科技计划资助项目(2021C065L)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.06.0359
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 3
Section: Algorithm Research & Explore
Pages: 671-675,688
Serial Number: 1001-3695(2023)03-005-0671-05

Publish History

[2022-10-12] Accepted Paper
[2023-03-05] Printed Article

Cite This Article

王伟, 张志莹, 郭杰龙, 等. 基于脑启发的类增量学习 [J]. 计算机应用研究, 2023, 40 (3): 671-675,688. (Wang Wei, Zhang Zhiying, Guo Jielong, et al. Brain-inspired class incremental learning [J]. Application Research of Computers, 2023, 40 (3): 671-675,688. )

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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