搜索资源列表
Blind-Source
- 基于超平面 欠定盲分离源信号的混合矩阵的估计-underdetermined Blind Source Separation
WE
- 稀疏条件下欠定盲分离，得到混合矩阵，恢复原信号-Underdetermined blind separation under sparse conditions
mangjiejuanji
- 信号处理的盲源分离算法，用于信号卷积混合盲分离，供大家参考一下。-Blind Source Separation of signal processing algorithms for signal convolution Blind separation, for your reference.
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- 很好的盲源分离程序，真的非常非常实用，试试吧。-very good blind separation programm
blind-speech-separation
- 完成欠定盲语音分离，源信号为3路输入，有2路麦克风，用c实现。-Underdetermined blind speech separation is completed, the source signal is 3 inputs, 2 mic, with c achieve.
fastica
- 简单的fastICA程序，基于matlab实现盲分离，比较实用。-FastICA simple procedure, based on matlab realize blind separation, more practical.
BSS
- 一种基于稀疏变量的欠定盲分离算法，很好用，大家试一下。-Underdetermined blind separation algorithm based on sparse variables
SINGNAL-SEPARATION
- 盲信号处理算法相关论文,对初学者来说很实用，毕业设计参考内容-Blind signal processing algorithms relevant papers, very useful for beginners, graduation design reference content
UniBSS
- 一种基于统一模型的盲信号分离matlab源代码，三路语音信号盲分离源程序-A unifying model for blind separation of independent sources
Blind-source-separation
- 用MATLAB实现d2d端的信号盲分离，分离出干扰信号与有用信号-MATLAB d2d the blind source separation, separate the disturbance signal and useful signal
57169speal
- 盲分离程序，利用FSATICA独立分量分析的方法实现了线性混合信号的盲分离-Blind separation procedures, the use FSATICA independent component analysis method to achieve a linear mixed-signal blind separation
negentropy
- 基于负熵的盲源分离算法，可以用于语音的盲分离，提高语音信号质量-Negative entropy algorithm based on blind source separation, can be used to blind separation of speech, improve the quality of voice signal
RLS
- 针对两路 QPSK 信号同频重叠的且存在频率漂移等单通道信号盲分离-Blind separation of single channel such as frequency drift and frequency shift in the same frequency of two QPSK signals
Sparse-blind-source-
- 盲源分离程序代码 用于信号处理和模态识别-Blind source separation program code for signal processing and modal identification
dspproject
- 对声音进行去噪，盲分离处理，并可进行变音，回音等特效处理，通过GUI界面集成-Sound denoising, blind separation processing, and can be accented, echo and other effects processing through the GUI interface integration
盲源分离
- 常用的盲分离算法有二阶统计量方法、高阶累积量方法、信息最大化（ Infomax ）以及独 立成分分析（ ICA ）等。这些方法取得最佳性能的条件总是与源信号的概率密度函数假设有关， 一旦假设的概率密度与实际信号的密度函数相差甚远，分离性能将大大降低。本文提出采用 核函数密度估计的方法进行任意信号源的盲分离，并通过典型算例与几种盲分离算法进行了 性能比较，验证了方法的可行性。(The commonly used blind separation algorithms include
2014-03-19-Focuss算法
- 主要实现源信号盲分离，注释比较清楚，能够运行，对于初学者帮助较大(The main source of blind separation of the signal, the note is relatively clear, able to run, for beginners to help larger)
ICA快速算法原理和程序
- FastICA算法是基于非高斯性最大化原则得到的一批处理算法。峭度和负熵都可以作为非高斯性的度量。(Advantages: applicable to any non-gaussian signal, blind separation algorithm with fast convergence speed and easy to use, without the need to choose the learning step, is the most widely used algorit
a_bad_geek-FastICA-master
- fastica算法，信号盲分离，专用于多通道混合数据的分离(FastICA algorithm, blind separation of signals, for the separation of multichannel mixed data)
用MATLAB来实现3个通道的语音盲源分离
- 盲分离算法，处理声音信号的分离，供语音识别使用(Blind separation algorithm, which handles the separation of sound signals, is used for speech recognition.)