The result of experiment shows that KICA is more accurate and robust than other conical ICA and PCA in the BBS.
实验表明在盲源信号分离中，基于核空间的ICA与其他典型ICA和PCA算法相比更具有准确性和鲁棒性。
Finally, the experimental and analytical results show that in face recognition KICA algorithm outperforms ica algorithm.
实验和分析结果表明，在人脸识别中，基于KICA的方法优于基于ICA的方法。
KICA with model selection step is applied to the task of removing ECG artifact from the EEG signal and the result shows KICA.
实验结果表明：经模型选择后的K ICA能成功分离脑电信号中的心电伪差。
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