长沙理工大学物理与电子科学学院
纸质出版:2025
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寻滔源, 李攀, 邹璨, 等. 基于LSTM-Conv1D-LIF的气体检测方法研究[J]. 传感器与微系统, 2025,(8):41-45.
寻滔源, 李攀, 邹璨, 等. 基于LSTM-Conv1D-LIF的气体检测方法研究[J]. 传感器与微系统, 2025,(8):41-45. DOI: 10.13873/J.1000-9787(2025)08-0041-05.
针对气体检测技术面临的时序数据特征提取与长期依赖捕捉难题,提出一种融合长短期记忆网络(LSTM)、一维卷积(Conv1D)与脉冲神经网络(SNN)的LSTM-Conv1D-LIF分类模型。该模型通过LSTM网络捕获气体响应信号的长期依赖关系,Conv1D提取局部时序特征,最终由SNN实现精确的分类决策。实验结果显示,该模型在乙醇、甲烷、乙烯和一氧化碳四分类任务中取得98.96%的准确率,较传统方法有明显提升。通过三种网络优势互补,为工业安全预警和环境监测提供了一种高鲁棒性的解决方案。
徐昊,章检明,王中鹏,张丽娟,迟梁,何成.基于电子鼻的深度卷积神经网络茯苓产地分类方法[J].传感器与微系统,2023(12).
刘浩,柴洪峰,孙权,云昕,李鑫.脉冲神经网络研究现状与应用进展[J].中国工程科学,2023(06).
刘旭,余隽,李中洲,魏广芬,黄正兴,朱慧超.用于苹果品质监测的多温度扫描电子鼻系统[J].传感器与微系统,2023(10).
马宏莉,王涛,李泊龙,曾敏,杨建华,杨志.多组分气体定量识别的电子鼻系统设计[J].传感器与微系统,2022(05).
Yingying Xue,Shimeng Mou,Changming Chen,Weijie Yu,Hao Wan,Liujing Zhuang,Ping Wang.A Novel Electronic Nose Using Biomimetic Spiking Neural Network for Mixed Gas Recognition[J].Chemosensors,2024.
State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China,State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China,State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China,State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China,Department of Bioengineering, Stanford University, Stanford, CA 94305, USA,State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China,Department of Chemical Engineering and Biotechnology, Cambridge University West Site, Philippa Fawcett Drive, Cambridge CB3 0AS, UK,State Key Laboratory of Industrial Control Technology, Institute of Cyber Systems and Control, Zhejiang University, Hangzhou 310027, Zhejiang, China.An optimized deep convolutional neural network for dendrobium classification based on electronic nose[J].Sensors and Actuators: A. Physical,2020.
Emre O. Neftci,Hesham Mostafa,Friedemann Zenke.Surrogate Gradient Learning in Spiking Neural Networks: Bringing the Power of Gradient-based optimization to spiking neural networks.[J].IEEE Signal Process. Mag.,2019.
Jiuxiang Gu,Zhenhua Wang,Jason Kuen,Lianyang Ma,Amir Shahroudy,Bing Shuai,Ting Liu,Xingxing Wang,Gang Wang,Jianfei Cai,Tsuhan Chen.Recent advances in convolutional neural networks[J].Pattern Recognition,2018.
Pablo Stoliar,Julien Tranchant,Benoit Corraze,Etienne Janod,Marie‐Paule Besland,Federico Tesler,Marcelo Rozenberg,Laurent Cario.A Leaky‐Integrate‐and‐Fire Neuron Analog Realized with a Mott Insulator[J].Advanced Functional Materials,2017.
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