文件名称:LVAICA_009
下载
别用迅雷、360浏览器下载。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
如迅雷强制弹出，可右键点击选“另存为”。
失败请重下，重下不扣分。
介绍说明－－下载内容均来自于网络，请自行研究使用
We consider an extension of ICA and BSS for separating
mutually dependent and independent components from two related data
sets. We propose a new method which first uses canonical correlation
analysis for detecting subspaces of independent and dependent components.
Different ICA and BSS methods can after this be used for final
separation of these components. Our method has a sound theoretical
basis, and it is straightforward to implement and computationally not
demanding. Experimental results on synthetic and real-world fMRI data
sets demonstrate its good performance.
mutually dependent and independent components from two related data
sets. We propose a new method which first uses canonical correlation
analysis for detecting subspaces of independent and dependent components.
Different ICA and BSS methods can after this be used for final
separation of these components. Our method has a sound theoretical
basis, and it is straightforward to implement and computationally not
demanding. Experimental results on synthetic and real-world fMRI data
sets demonstrate its good performance.
(系统自动生成,下载前可以参看下载内容)
下载文件列表
LVAICA_009.pdf