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dependentcomponent
- 本文简要地回顾了ICA的发展历史和主要算法，综述了它在脑电信号处理中的应用及研究进展，并指出了需要进一步研究解决的问题。-This article briefly reviews the history of the development of the ICA algorithm EEG signal processing applications and research progress, and pointed out the need for further research to s
fICAAraro
- 用于脑电信号特征提取的InfoMax Algorithm Bassed on ICA；也能稍作改动用于其他信息提取。 -Feature extraction for EEG InfoMax Algorithm Bassed on ICA minor modifications for other information extraction.
arsvm2
- 利用ar模型和近似熵方法对癫痫脑电信号进行识别处理-Ar model and approximate entropy method epileptic EEG recognition processing
ar-model
- 几篇有关利用ar模型对癫痫脑电信号进行识别的英文文章，比较权威，是参考的好资料-Few articles about the use of ar model of epileptic EEG recognition of English articles, more authoritative reference information
EEG
- 脑电特征分析与研究，为临床脑电信号的诊断提供一定的理论考。-EEG analysis and research, and to provide a theoretical test for the diagnosis of clinical EEG.
threhold
- 对脑电信号的时域波形进行阈值检测，识别特征脑电-EEG time-domain waveform threshold detection
brain-signal-process
- 脑电信号的时域、频域、时频域分析算法 阈值分隔、模式识别算法-EEG time domain, frequency domain, time and frequency domain analysis algorithm threshold separated, pattern recognition algorithms
FFT
- 对脑电信号的频谱分析，分析脑电信号的功率谱特征-The spectral analysis of the EEG power spectrum analysis of EEG
xiangguan
- 对脑电信号进行相关计算，从而进行相关匹配-EEG calculated correlation matching
PDCX
- 进行脑电信号处理，得到是是32个导联的信号-EEG signal processing, Yes Yes 32-lead signal
filter
- 对脑电信号进行各种滤波处理,包括高通、低通、带通-Various filtering EEG signal processing, including high-pass, low-pass, band-pass
cancelling-noise
- 利用自适应滤波来滤除脑电信号采集过程中的50Hz工频干扰-Filter the power line interference based on adaptive filter for EEG
PDC-analysis
- 利用偏直接一致（PDC）指数分析同步采集的脑电信号和肌电信号之间的信息传递方向 -Analysis the information transfer direction btween synchronous EEG and EMG
gasvm
- 利用遗传算法对SVMk进行优化,并将其用于脑电信号的分类中-By using the genetic algorithm to optimize SVMk, and use it to the classification of the eeg signals
jinsishang
- 应用matlab分析脑电信号的非线性动力学中的近似熵-Application matlab in the analysis of the nonlinear dynamics of the EEG approximate entropy
2011-03-27-BCT
- 脑电信号测度计算，复杂网络研究的不同之处在于首先从统计角度考察网络中大规模节点及其连接之间的性质，这些性质的不同意味着不同的网络内部结构，而网络内部结构的不同导致系统功能有所差异。-EEG signal
xinhaofenlei
- 脑电信号的特征提取与分类，大家可以查阅，很有帮助的-EEG feature extraction and classification, we can access helpful
xiaobo-svm
- 关于脑机接口的文献，基于SVM和小波分析的脑电信号分类方法-Literature on brain-computer interface the EEG classification method based on SVM and Wavelet Analysis
EEG--classification
- 脑电信号的提取和特征分类还有滤波处理，适用于脑机接口技术中-EEG extraction and feature classification filtering process, applied to brain-computer interface technology
ND
- 毕业设计非常有用的脑电信号，本人亲测，效果不错，贡献给大家。-Graduate design very useful EEG, I pro-test, the effect is good, to the party.