搜索资源列表
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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
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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
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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.
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核ICA的工具箱，用于独立分分量分析，盲源信号分离（BSS）-nuclear ICA toolbox for independent sub-component analysis, Blind Source Separation (BSS)
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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.
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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. Networks found on a trip.
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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 each other, mean signal indepen
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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.
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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
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一种新的ICA算法，能够很好地对一维信号进行盲源分离，并有例程,A new ICA algorithm, very good to be able to one-dimensional signals, blind source separation, and have routine
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matlab编写的，盲源分离的程序汇总，学习信号处理非常有用-matlab written summary of blind source separation program, learning is very useful signal processing
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一个关于联合对角化盲源分离算法的SOBI算法，非常好-One on the joint diagonalization for blind source separation algorithm SOBI algorithm, very good! !
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基于MATLAB的fastica算法的实现,有完整源代码。这是一个关于盲源分离独立成分分析方法fastICA的软件包，给大家分享一下，完整的matlab代码。-MATLAB-based fastica algorithm, a complete source code. This is a blind source separation independent component analysis (ICA) of the package, to share with you, complete
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on time domain blind source separation implementation
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This file implements the Multi User Kurtosis Algorithm for Blind Source Separation (see [1] for more details about the method).
The zip file contains:
- the one_shot.m scr ipt file
- the MUK_algorithm.m function
The one_shot.m file
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In frequency-domain blind source separation (BSS) for speech with independent component analysis (ICA), a practical parametric Pearson distribution system is used to model the distribution of frequency-domain source signals.-In frequency-domain blin
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提出一种新的盲分离标准，基于这种标准构建横向反馈的线性前馈神经网路，并给出理论分析与实验结果-We presents a new necessary and sufficient condition for
the blind separation of sources having non-zero kurtosis,
from their linear mixtures. It is shown here that a new
blind separation criterion
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《基于白化旋转技术的盲分离算法文章及程序》自己写的针对文章的仿真，基本符合要求还有很多不足-blind source separation
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盲源分离的新算法，非常经典的英文文献，值得一读。-Blind source separation algorithm, a classic of English literature worth reading.
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直接运行Demo文件即可，本算法案例是两源信号卷积混合，基于同一信号相邻频点能量相关的方法对频域盲源分离信号进行排序(The demo file can be run directly. The case of this algorithm is the convolution mixing of two source signals. The Blind Source Separation (BSS) signals in frequency domain are sorted based o
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