ICA算法The algorithm is equivalent to Infomax by Bell and Sejnowski 1995 [1] using a maximum likelihood formulation. No noise is assumed and the number of observations must equal the number of sources. The BFGS method [2] is used for optimization. The

：由于许多传统的去噪方法在强背景噪声情况下提取声音信号的能力变弱甚至失效， 提出 应用独立成分分析( I C A) 方法对声音信号进行特征提取， 并证明了这种 I C A 变换能增强语音和音 乐信号的超高斯性． 在此基础上， 应用 I C A基函数作为滤波器， 通过阈值化的去噪方法对含有强高 斯背景噪声的声音信号进行去噪仿真实验． 结果表明， 本方法明显优于传统的均值滤波和小波去噪 方法， 为强背景噪声下弱信号的检测提供 了新的途径．-: As many of the t

基于最大信噪比的ICA算法，在盲信号分离中用处比较大-ICA algorithm based on maximum signal to noise ratio, useful in blind signal separation in the larger

把ICA和NLM结合一起的去噪算法程序。先对噪声图像进行ICA处理，然后用NLM滤波对处理结果进行二次处理。效果比直接用NLM对噪声图片滤波要好。-ICA and NLM combined with the denoising algorithm program. Firstly, the noise image is processed by ICA, and then the results are processed by two times with NLM filter. Effect

一些关于脑电信号中噪声的去除ICA算法的实现，所用脑电信号为SSVEP试验。只是一些小程序，还有很多不足，望补充-Some implementations on removing ICA algorithm of noise in EEG, EEG is used SSVEP test. Just some small programs, there are many shortcomings, hope others added this