共查询到18条相似文献，搜索用时 187 毫秒
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随着科技的进步,三维运动捕捉系统越来越多的进入到角色动作的创作中。给动画中角色动作的创作带来了极大地便利,从而大大的降低了动画制作的成本。想要利用好三维运动捕捉系统需要认识各系统的优缺点,有的放矢的利用三维运动捕捉系统进行科学研究和艺术创作。 相似文献
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WOLPAW等人在2012年出版的著作《Brain-computer interfaces:principles and practice》中指出:脑机接几(BCI)是将中枢神经系统活动转换为人工输出的系统,它能替代、修复、增强、补充或改善中枢神经系统的正常输山,从而改变中枢神经系统与内外环境之间的交互作用:其核心为建立大脑与外部环境之间的特殊通讯系统.作为一种新兴的交叉技术,BCI近年来得到了快速发展,并日趋完善. 相似文献
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动力系统类属性质研究着眼于对某一类系统的运动概括出来的共性.已知经典可积系统的运动是规则的,可用解析函数来描述,而不可积系统则相反.从简谐振子入手,指出动力对称性群的存在是能有规则运动的前提,还把这一概括出来的抽象陈述推广到了更一般的经典情形.量子力学是在哈密顿力学基础上,注入微观系统的特殊要求而建立起来的,所以这一关于经典规则运动的陈述可以推广到相应的量子情形,从而更好地阐明了量子经典对应的涵义 相似文献
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利用Pro/E软件对真空泵进行了装配设计,并利用Pro/E软件的Pro/Mechanism模块对真空泵进行了运动仿真。机构运动仿真技术是通过计算机技术来模拟真实机构的运动过程,同时借助系统建模技术和可视化技术来实现机构运动仿真。 相似文献
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针对高中物理“平抛运动实验”中描点效果不理想这一缺点,在原来实验装置的基础上进行改进,利用平行光把小球的影子投射到带有坐标的纸上,方便找点;由于小球运动较快,对于同一个点,可采用逐步缩小范围的方法确定点和坐标,改进后,实验装置操作简便,运动轨迹描绘准确. 相似文献
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Xiao Zhang Dongrui Wu Lieyun Ding Hanbin Luo Chin-Teng Lin Tzyy-Ping Jung Ricardo Chavarriaga 《国家科学评论(英文版)》2021,8(4)
An electroencephalogram (EEG)-based brain–computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled individuals, e.g. amyotrophic lateral sclerosis patients, who have no other effective means of communication with another person or a computer. Most studies so far focused on making EEG-based BCI spellers faster and more reliable; however, few have considered their security. This study, for the first time, shows that P300 and steady-state visual evoked potential BCI spellers are very vulnerable, i.e. they can be severely attacked by adversarial perturbations, which are too tiny to be noticed when added to EEG signals, but can mislead the spellers to spell anything the attacker wants. The consequence could range from merely user frustration to severe misdiagnosis in clinical applications. We hope our research can attract more attention to the security of EEG-based BCI spellers, and more broadly, EEG-based BCIs, which has received little attention before. 相似文献
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简要介绍了Matlab工程软件的特点以及《信号与系统》课程教学中存在的问题,并通过几个典型实例来重点研究Matalb在信号时域分析、信号频域分析、LTI系统时域分析、LTI系统复频域分析及LTI系统z域分析中的应用。实践证明,利用该软件进行仿真,学生能更深刻地理解教学内容。 相似文献
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《Information processing & management》2022,59(5):103001
Brain–computer interface (BCI) is a promising intelligent healthcare technology to improve human living quality across the lifespan, which enables assistance of movement and communication, rehabilitation of exercise and nerves, monitoring sleep quality, fatigue and emotion. Most BCI systems are based on motor imagery electroencephalogram (MI-EEG) due to its advantages of sensory organs affection, operation at free will and etc. However, MI-EEG classification, a core problem in BCI systems, suffers from two critical challenges: the EEG signal’s temporal non-stationarity and the nonuniform information distribution over different electrode channels. To address these two challenges, this paper proposes TCACNet, a temporal and channel attention convolutional network for MI-EEG classification. TCACNet leverages a novel attention mechanism module and a well-designed network architecture to process the EEG signals. The former enables the TCACNet to pay more attention to signals of task-related time slices and electrode channels, supporting the latter to make accurate classification decisions. We compare the proposed TCACNet with other state-of-the-art deep learning baselines on two open source EEG datasets. Experimental results show that TCACNet achieves 11.4% and 7.9% classification accuracy improvement on two datasets respectively. Additionally, TCACNet achieves the same accuracy as other baselines with about 50% less training data. In terms of classification accuracy and data efficiency, the superiority of the TCACNet over advanced baselines demonstrates its practical value for BCI systems. 相似文献
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What can the brain–computer interface (BCI) do? Wearing an electroencephalogram (EEG) headcap, you can control the flight of a drone in the laboratory by your thought; with electrodes inserted inside the brain, paralytic patients can drink by controlling a robotic arm with thinking. Both invasive and non-invasive BCI try to connect human brains to machines. In the past several decades, BCI technology has continued to develop, making science fiction into reality and laboratory inventions into indispensable gadgets. In July 2019, Neuralink, a company founded by Elon Musk, proposed a sewing machine-like device that can dig holes in the skull and implant 3072 electrodes onto the cortex, promising more accurate reading of what you are thinking, although many serious scientists consider the claim misleading to the public. Recently, National Science Review (NSR) interviewed Professor Bin He, the department head of Biomedical Engineering at Carnegie Mellon University, and a leading scientist in the non-invasive-BCI field. His team developed new methods for non-invasive BCI to control drones by thoughts. In 2019, Bin’s team demonstrated the control of a robotic arm to follow a continuously randomly moving target on the screen. In this interview, Bin He recounted the history of BCI, as well as the opportunities and challenges of non-invasive BCI. 相似文献
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《Information processing & management》2023,60(3):103262
Smart wheelchairs based on brain–computer interface (BCI) have been widely utilized recently to address certain mobility problems for people with disability. In this paper, we present SmartRolling, an intuitive human–machine interaction approach for the direct control of robotic wheelchair that jointly leverages EEG signals and motion sensing techniques. Specifically, SmartRolling offers two wheelchair-actuation modes for users with different physical conditions: (1) head motion only — people who are severely disabled but able to do basic tasks using eyes and head, and (2) head and hands motion — in addition to type 1, people who can use functioning hands/arms for extra tasks. The system issues operation commands by recognizing different EEG patterns elicited by motor execution (ME) tasks including eye blink, jaw clench, and fist open/close, while at the same time estimates users’ steering intentions based on their facing direction by leveraging inertial measurements and computer vision techniques. The experiment results demonstrate that the proposed system is robust and effective to meets the individual’s needs and has great potential to promote better health. 相似文献
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The linear canonical transform (LCT) has been shown to be a powerful tool for optics and signal processing. Many theories for this transform are already known, but the uniform sampling theorem, as well as the sampling rate conversion theory about arbitrary lattices sampling in the LCT domain are still to be determined. Focusing on these issues, this paper carefully investigates arbitrary lattices sampling, the sampling with separable matrices and nonseparable matrices, to obtain uniform sampling theorem and the sampling rate conversion theory in the LCT domain. Firstly, the spectral expression of the discrete-time signal sampled via arbitrary lattice is deduced in the LCT domain. Based on it we propose the alias-free sampling relationship between two matrices and present the perfect reconstruction expressions for bandlimited signals in the LCT domain. Secondly, for further research on discrete signals to obtain sampling rate conversion theory, we define the multidimensional discrete time linear canonical transform (MDTLCT), as well as the convolution for the MDTLCT. Thirdly, the formulas of multidimensional interpolation and decimation via integer matrices in the LCT domain are derived. Then, based on the results of interpolation and decimation, we make analyses of the sampling rate conversion via rational matrices in the LCT domain, including spectral analyses and the formulas in time domain. Finally, simulation results and the potential applications of the theories are also presented. 相似文献
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本文介绍了齿轮振动信号的时域分析与频域分析的理论基础。针对齿轮常见故障原因和类型,引出了齿轮故障诊断的常用方法,并选用经典的振动分析法,利用MATLAB信号分析功能,对齿轮故障信号的时域和频域分析进行了详尽的阐述。本文对齿轮故障诊断有一定的指导意义。 相似文献
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In this paper, the stability problem of discrete-time systems with time-varying delay is considered. Some new stability criteria are derived by using a switching technique. Compared with the Lyapunov–Krasovskii functional (LKF) approach, the method used in this paper has two features. First, a switched model, which is equivalent to the original system and contains more delay information, is introduced. It means that the criteria obtained by using the LKF method can be regarded as stability criteria for the switched system under arbitrary switching. Second, when the switching signal is known, the stability problem for the switched model under constrained switching is considered and piecewise LKFs are adopted to obtain stability criteria. Since constrained switching is less conservative than arbitrary switching if the switching signal is known, one can know that the obtained results in this paper are less conservative than some existing ones. Two examples are given to illustrate the effectiveness of the obtained results. 相似文献