搜索资源列表
flexica
- 这是实际环境中语音信号盲分离的最新程序代码，用于语音信号独立分量分析ICA。解压后运行，输入录制的混合语音信号即可看到结果。-this is the actual environment of the speech signal separation blind to the latest code, Voice Signal for independent component analysis ICA. Unpacked operation, the importation of record
FastICA
- FastICA算法，用于信号的独立分量分析，在ICA的基础上加快了收敛速度，有更高的效率！并且增加了图象界面，使用方便！-FastICA algorithm, the signal for an independent component analysis, at the ICA on the basis of accelerating the convergence rate, a more efficient! And to increase the image user interface
icalab
- ICA:独立分量分析，基于MATLAB语言-ICA : Independent component analysis, based on MATLAB
SpeakerrecognitionsystembasedonICAandVQ
- 一篇介绍 基于独立分量分析和矢量量化的说话人识别 的ＣＡＪ文档
f2007421165913
- 运用独立分量分析的特征矩阵的联合近似对角化（JADE法） 希望有用
chengxu
- 这是关于独立分量分析的源代码，非常好用，欢迎大家下载
ICA_JADE
- 基于独立分量分析的JADE算法，非常实用。
BSS_FastICA_matlab.用于盲信号分离的独立分量分析和主元分量分解
- 用于盲信号分离的独立分量分析和主元分量分解以及独立分量分解的代码,For Blind Signal Separation of independent component analysis and principal component decomposition and independent component decomposition of the code
FastICA_24
- 改进的独立分量分析,在以往的独立分量分析中加入核函数，避免其缺陷，更好的分离信号。-Improvement of independent component analysis (ica), in the past the independent component analysis (ica) adding kernel function, avoid its defects, better separated signal.
fp
- 基于ICA的独立分量分析，目标函数是负熵，快速不动点算法-ICA-based independent component analysis, the objective function is negative entropy, fast fixed-point algorithm
work
- 基于负熵的FASTICA的不动点算法，并行提取信号，独立分量分析-Based on negative entropy FASTICA the fixed point algorithm, parallel extract the signal, independent component analysis
qiaodu
- 基于峭度的独立分量分析，包括并行提取和串行提取的程序-ICA based on kurtosis analysis, including parallel and serial extraction procedures for extracting
ML
- 基于最大似然估计的独立分量分析算法，包括随机梯度算法，相对梯度算法，快速不动点算法3个程序-Based on maximum likelihood estimation of independent component analysis algorithms, including stochastic gradient algorithm, the relative gradient algorithm, fast fixed-point algorithm for three programs
ica
- 一独立分量分析是在研究盲源分离过程中出现的一种全新的数据分析和信号处理方法 -An independent component analysis in the study of blind source separation is the process of the emergence of a new data analysis and signal processing methods
my_ICA
- 基于峭度的快速独立分量分析的程序，内含三个源信号-Based on kurtosis fast independent component analysis program, containing three source signal
MutualInformationICA
- 互信息独立分量分析，克服传统独立分量分析的缺陷，很好的实现原信号波形恢复。-Mutual information independent component analysis, to overcome the defects of traditional independent component analysis, it is good to realize the original signal recovery.
work
- 对三路信号进行分离，基于峭度和基于负熵的独立分量分析（ICA）-The three way signal separation, based on the kurtosis and independent component analysis (ICA) based on negative entropy
NewICA_2014
- 独立分量分析算法（ICA）可以用于信号分解，数据处理等-Independent component analysis (ICA) can be used to decompose the signal, data processing
BKSA_BSS
- 一种新的基于峰度的盲源分离开关算法（附参考文章），无需假设源信号的概率密度函数, 可直接对独立分量分析中的激活函数进行自适应学习。-A New kurtosis switching algorithm for blind source separation (with reference to the article), without assuming that the probability density function of the source signal, independent
quimie-V6.1
- 进行逐步线性回归，迭代自组织数据分析，最大信噪比的独立分量分析算法。- Stepwise linear regression, Iterative self-organizing data analysis, SNR largest independent component analysis algorithm.