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Akademický článek

A constitutive model based on energy density for power-law variable thickness plates and its application

Autor: Miao-xia Xie, Qian-lang Huang, Peng Zhang, Xin-tao Ren, Feng-wei Gao, Ling Li, Yue-ming Li

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-16 (2024)

Abstract Variable thickness plates are relatively common structure in large-scale transportation equipment such as aerospace and ships. Due to their high running speed and large structural dimensions, such structures are usually induced high-frequenc

Externí odkaz: https://doaj.org/article/490fe13b39df44469e0a595e0b156eef

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The Brain-Inspired Cooperative Shared Control Framework for Brain-Machine Interface

Autor: Yang, Junjie, Liu, Ling, Zheng, Shengjie, Qian, Lang, Gao, Gang, Chen, Xin, Li, Xiaojian

In brain-machine interface (BMI) applications, a key challenge is the low information content and high noise level in neural signals, severely affecting stable robotic control. To address this challenge, we proposes a cooperative shared control frame

Externí odkaz: http://arxiv.org/abs/2210.09531

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An Adaptive Contrastive Learning Model for Spike Sorting

Autor: Qian, Lang, Zheng, Shengjie, Deng, Chunshan, Yang, Cheng, Li, Xiaojian

Brain-computer interfaces (BCIs), is ways for electronic devices to communicate directly with the brain. For most medical-type brain-computer interface tasks, the activity of multiple units of neurons or local field potentials is sufficient for decod

Externí odkaz: http://arxiv.org/abs/2205.11914

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An Introductory Review of Spiking Neural Network and Artificial Neural Network: From Biological Intelligence to Artificial Intelligence

Autor: Zheng, Shengjie, Qian, Lang, Li, Pingsheng, He, Chenggang, Qin, Xiaoqin, Li, Xiaojian

Publikováno v: 8th International Conference on Artificial Intelligence 2022

Recently, stemming from the rapid development of artificial intelligence, which has gained expansive success in pattern recognition, robotics, and bioinformatics, neuroscience is also gaining tremendous progress. A kind of spiking neural network with

Externí odkaz: http://arxiv.org/abs/2204.07519

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A Spiking Neural Network based on Neural Manifold for Augmenting Intracortical Brain-Computer Interface Data

Autor: Zheng, Shengjie, Li, Wenyi, Qian, Lang, He, Chenggang, Li, Xiaojian

Publikováno v: 31st International Conference on Artificial Neural Networks 2022

Brain-computer interfaces (BCIs), transform neural signals in the brain into in-structions to control external devices. However, obtaining sufficient training data is difficult as well as limited. With the advent of advanced machine learning methods,

Externí odkaz: http://arxiv.org/abs/2204.05132

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