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面向BCI的机器学习与信号处理工具

Machine Learning and Signal Processing Tools for BCI
课程网址: http://videolectures.net/bbci09_blankertz_muller_mlasp/  
主讲教师: Klaus-Robert Müller, Benjamin Blankertz
开课单位: 德国柏林工业大学
开课时间: 2009-08-10
课程语种: 英语
中文简介:
我们将首先从机器学习和信号处理的角度简要概述脑-计算机接口。特别是要展示现有数据的丰富、复杂和困难,这是一个真正巨大的挑战:实时处理受噪声污染的多变量数据流,准确区分神经电活动。然后,我们将详细讨论现代BCI系统中使用的数据分析链的组成部分,涉及从预处理和特征提取、自适应与固定分类以及反馈设计的各个方面。
课程简介: We will first provide a brief overview of Brain-Computer Interface from a machine learning and signal processing perspective. In particular showing the wealth, the complexity and the difficulties of the data available, a truly enormous challenge: In real-time a multi-variate very strongly noise contaminated data stream is to be processed and neuroelectric activities are to be accurately differentiated. We will then in detail discuss the components of the data analysis chain employed in modern BCI systems, spanning all aspects from preprocessing and feature extraction, adaptive vs. fixed classification and feedback design.
关 键 词: BCI; 机器学习; 信号处理工具
课程来源: 视频讲座网
最后编审: 2020-09-21:heyf
阅读次数: 46