搜索资源列表
amuse
- 这是利用特征值分解的盲源分离的源函数文件，可以直接调用-This is the eigenvalue decomposition of Blind Source Separation of source function, can be called directly
bss_toolbox
- 这是一个盲源分离的应用程序，其中还包括做实验用的各种数据-This is a blind source separation applications, which also includes an experiment with the various data
FastICA25
- 快速ICA算法，在盲源分离中有很大的用处。-fast algorithm, the blind source separation is very useful.
amu
- 基于盲源分离的scilab程序，可编译成matlab，使用时声音信号以及路径自行修改-Blind Source Separation based on the SciLab procedures, which compiled Matlab. the use of voice signal and the path to amend its own
infomax2
- matlab盲源分离informax程序-Matlab Blind Source Separation procedures informax
acdc
- 联合对角化方法，用于对多个矩阵同时进行联合对角化，主要用处是盲源分离。-joint diagonalization method for the same time on a number of joint matrix diagonalization, the main use is Blind Source Separation.
ica_ng
- 自己编的，基于自然梯度的盲源分离算法，如果想对自然梯度有所了解，可以参考Amari的经典文章。网络上一搜就行。-own series, based on the natural gradient algorithm blind source separation, if you want to understand the natural gradient. Amari can refer to the classic article.
muatual_information_ICA
- 互信息盲源分离，这基于这么一个事实，混合信号的互信息最小时，意味着信号独立。可以参考有关书籍。在google里面，搜索mutual information blind source separation.即可搜到文章。-mutual information Blind Source Separation, such a fact-based, mixed-signal information in the most hours of e
convolutive
- 卷积盲源分离，采用matlab编程，带有说明文档。-convolution Blind Source Separation using Matlab programming, with documentation.
bss-sond
- 提出了一种新的自适应盲源分离算法。在无噪音实时两源两传感器的情况下, 一旦观 测信号被白化, 只需要辨识一个特定的旋转矩阵就可以完成盲源分离, 并给出了能表征该旋转矩阵的角的自适应估计器。仿真结果表明, 当满足源峭度和不为零的条件时, 这种方法是一种稳定的和有效的分离算法。-proposes a new adaptive algorithm for blind source separation. In the absence of
maxkurtica
- 基于峭度极大的ＩＣＡ算法 ，用于盲源分离-Kurtosis great ICA algorithm for the Blind Source Separation
EMD_IEEE_PLANS_06
- 在IEEE上下载到的，EMD和盲源分离的经典文章，对EMD的使用，和应用也是大有裨益-in IEEE downloaded to the EMD and Blind Source Separation of the classic article on the use of EMD. and applications are also of great benefit
relnwt021203
- 该代码为盲源分离中的相对牛顿法，收敛性能稳定，分离效果优越，值得借鉴。
qqqqq
- ：独立成分分析 ( I C A)在国内尚属一门新型的方法 介绍了I C A的原理及其算法 ，然后介绍了该算法在盲源 信号分离中的具体应用，并将此方法 与主成分方洼 ( P C A)进行了比较-: Independent Component Analysis (ICA) in China is a new method to introduce the principle of the ICA and its algorithm,
source_model
- 盲信号分离的源信号模型，要更好的了解和利用时间序列的内在时间结构和复杂特性，通常可以采用相应的数学模型区近似描述各种类型的数据，该程序采用泛化自回归模型来产生盲源信号-Blind signal separation of the source signal model, we must better understand and leverage the structure of time series Neizai He Fuzate
mfa
- 用于盲信号分离的原代码，可以根据输入源信号的基本统计特征,由观测数据进行信号分离,最终恢复出源信号。 -Blind signal processing has become an emerging subject in signal processing in these years, which depends on the source signal statistical characteristics to separat
bssg
- 在windows matlab环境下实现卷积模型下的信号盲源分离-In matlab simulation environment， convolutive BSS problem is solved.
gradient1
- 本程序用自然梯度算法实现源信号的分离，给出了平均串音误差(This program uses natural gradient algorithm to achieve the separation of source signals, and gives the average crosstalk error)
DUET
- 介绍了DUET盲源分离方法，可以仅使用两个混合信号分离任何数目的源分离方法。该 方法适用于源信号W-不相交正交的情况。(T the DUET Blind Source Separation method which can separate any number of sources using only two mixtures. The method is valid when sources are W-disjoint ort
频域盲解卷积
- 该算法可以实现在频域解解卷积，包含排序算法，亲测好用(The algorithm can realize deconvolution in frequency domain, including sorting algorithm, which is easy to test)