Xiong Xinbing, Chen Yaguang
School of Electrical and Informatics Engineering, South-Center University for Nationalities, Wuhan 430074, China.
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2007 Aug;24(4):727-31.
A new approach is put forward for reducing the number of trials required for the extraction of the brain event related potentials (ERPs). The approach is developed by combining both the subspace methods and lift wavelet transform. First, the signal subspace is estimated by applying the singular value decomposition (SVD) to an enhanced version of the raw data obtained by orthonormal projection of the raw data onto the estimated signal subspace. At the same time, the colored noise is whitened. Next, the ERPs are extracted by lift wavelet construction of the enhanced version. Simulation results show that combination of both the subspace methods provides much better capability than does each of them. The experiments showed that the practical results were good.
提出了一种新方法来减少提取脑事件相关电位（ERP）所需的试验次数。该方法是通过结合子空间方法和提升小波变换开发的。首先，通过对原始数据进行正交投影到估计信号子空间上得到的增强版原始数据应用奇异值分解（SVD）来估计信号子空间。同时，对有色噪声进行白化处理。接下来，通过对增强版进行提升小波构造来提取ERP。仿真结果表明，子空间方法的结合比单独使用其中任何一种方法都具有更好的性能。实验表明实际结果良好。
