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Jiaming Chen

Publications
5
Citations
40
Publications by Year
20202022
Co-Authors:
Show All Co-Authors (14)
Image of author Jiaming Chen

Jiaming Chen

Affiliation

Faculty of Information Technology
Beijing University of Technology
Beijing, China

Publication Topics

Biography

Jiaming Chen was born in Beijing, China, in 1994. He received the M.S. degree in software engineering from Capital Normal University, Beijing, in 2019. He is currently pursuing the Ph.D. degree in computer science with the Beijing University of Technology.,In 2018, he was a Researcher and an Assistant Tutor with the Big Data College, Huike Education Corporation. From 2016 to 2018, he was the Frontend Architect of Chengdu iDelta Technology Company Ltd. His research interests include artificial intelligence, brain computer interface, and data mining. He received the Scholarship of Capital Normal University from 2016 to 2018 and won the Third Prize in the contest of Lan Qiao Cup in 2017.(Based on document published on 5 November 2020).
Publications
5
Citations
40
Publications by Year
20202022
Co-Authors:
Show All Co-Authors (14)
Author's Published Works

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MCFHNet: Multi-Channel Fusion Hybrid Network for Efficient EEG-fNIRS Multi-modal Motor Imagery Decoding

Jiaming Chen;Dan Wang;Bo Hu;Weibo Yi;Meng Xu;Dingrui Chen;Qing Zhao

2022 44th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Year: 2022 | Conference Paper |
Cited by: Papers (3)
Motor Imagery-based Brain Computer Interface (MI-BCI) is a typical active BCI with a main focus on motor intention identification. Hybrid motor imagery (MI) decoding methods that based on multi-modal fusion of Electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), especially deep learning-based methods, become popular in recent MI-BCI studies. However, the fusion strategy ...Show More

MCFHNet: Multi-Channel Fusion Hybrid Network for Efficient EEG-fNIRS Multi-modal Motor Imagery Decoding

Jiaming Chen;Dan Wang;Bo Hu;Weibo Yi;Meng Xu;Dingrui Chen;Qing Zhao

Year: 2022 | Conference Paper |

Filter Bank Sinc-ShallowNet with EMD-based Mixed Noise Adding Data Augmentation for Motor Imagery Classification

Jiaming Chen;Weibo Yi;Dan Wang

2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Year: 2021 | Conference Paper |
Cited by: Papers (3)
Motor imagery-based brain computer interface (MI-BCI) is a representative active BCI paradigm which is widely employed in the rehabilitation field. In MI-BCI, a classification model is built to identify the target limb from MI-based EEG signals, but the performance of models cannot meet the demand for practical use. Lightweight neural networks in deep learning methods are used to build high perfor...Show More

Filter Bank Sinc-ShallowNet with EMD-based Mixed Noise Adding Data Augmentation for Motor Imagery Classification

Jiaming Chen;Weibo Yi;Dan Wang

Year: 2021 | Conference Paper |

Fuzzy Controllers With Neural Network Predictor for Second-Order Linear Systems With Time Delay

Jingwei Liu;Xinyu Tao;Xueyang Ma;Kangmin Feng;Jiaming Chen

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (8)
Artificial intelligence methods are widely applied in advanced control practices such as fuzzy calculation-based intelligent control method, neural network-based predictive control method, etc. Control performances are expected to be improved such as: faster control speed, smaller steady-state error, and less repeated manual tuning workloads in harmful environments for engineers. Main works are as...Show More

Fuzzy Controllers With Neural Network Predictor for Second-Order Linear Systems With Time Delay

Jingwei Liu;Xinyu Tao;Xueyang Ma;Kangmin Feng;Jiaming Chen

Year: 2020 | Volume: 8 | Journal Article |

Multiple Linear Regression Prediction and Wavelet Neural Network Based Intelligent Online Tuning Control Method

Jingwei Liu;Mengxuan Zhao;Guanchen Li;Jiaming Chen

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (7)
Manual-based parameters tuning methods of control system are widely used in many industrial fields. However, better control performances such as faster control speed, more stable, less workload and safer working conditions are expected. Therefore, artificial intelligent based improved classical control (AI-CC) is highly valued in control fields. Main works are as follows: Firstly, wavelet neural n...Show More

Multiple Linear Regression Prediction and Wavelet Neural Network Based Intelligent Online Tuning Control Method

Jingwei Liu;Mengxuan Zhao;Guanchen Li;Jiaming Chen

Year: 2020 | Volume: 8 | Journal Article |

NARX Prediction-Based Parameters Online Tuning Method of Intelligent PID System

Jingwei Liu;Tianyue Li;Zheyu Zhang;Jiaming Chen

IEEE Access
Year: 2020 | Volume: 8 | Journal Article |
Cited by: Papers (19)
Control parameters of classical control system are expected to be online tuned and optimized by intelligent methods, in order to improve performance and help engineers reduce a lot of repetitive work in dangerous and harmful working environments. Main ideas and works of this paper are as follows:Firstly, change ratio based expert PID control method (EA-PID) is proposed to expand range of control p...Show More

NARX Prediction-Based Parameters Online Tuning Method of Intelligent PID System

Jingwei Liu;Tianyue Li;Zheyu Zhang;Jiaming Chen

Year: 2020 | Volume: 8 | Journal Article |

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