搜索资源列表
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
cubica34
- 该算法以全局最优的方式实现盲源分离，程序调用说明：x为观测信号，y为估计信号-The global optimization algorithm to achieve blind source separation approach, the program calls Descr iption: x for the observed signal, y is estimated signals
maxkurtica
- 一种新的基于峭度的盲源分离开关算法。程序调用说明：该算法程序调用格式为[y,w]=bksa(x),其中x是一个n*T的数据矩阵，y是估计出的源信号矩阵，w是n*n分离矩阵。-A new kurtosis-based switch algorithm for blind source separation. Program calls Note: The algorithm program calls the format [y, w] = bksa (x), where n* T x is a
BSS_Demo4SP_20Mar2k5
- 一个盲源分离的GUI界面，本程序可完成语音信号的独立分量分析。-A blind source separation GUI interface, this program can be completed independent component analysis of speech signals.
whiting-procedue
- 盲信号处理中得白化处理实验，是盲源分离中得重要程序-I m glad to show a very important procedue in BSS(blind source separate) with you.Whiting procedue is a important and normal.
Bmybbsssl
- 盲信号分离是当前信号处理研究的热点课题之一，在无线数据通信、医学、语音和地震信号处理等领域有着广阔的应用前景。一种基于负熵最大的FastICA算法用于实现盲信号分离。。该方法的基本思路是以非高斯信号为研究究对象，在独立性假设的前提下，对多路观测信号进行盲源分离。在满足一定的条件下，能够从多路观测信号中，较好地分离出隐含的独立源信号。 -Blind signal separation is one of the hot topics of signal processing research
FastICA_25
- 可进符合信号行的快速盲源分离，进而实现将复杂信号快速分离的效果。-Coincidence signal line fast blind source separation, so as to realize the effect of the rapid separation of the complex signal.
8
- ICA算法 实现盲源分离三种信号的分析-Blind Source Separation ICA algorithm analyzes three signals
nonnegativeICAexample
- 非负独立分量盲源信号的分离方法是一种很简单的盲源分离方法-Non-negative independent component blind source separation method is a very simple blind source separation methods
psorfid
- 可以实现粒子群算法与盲源分离算法的结合，比较方便。源信号可以随便替换-PSO algorithm can be achieved with the combination of blind source separation algorithms, more convenient. Source signal can be easily replaced
fastica
- 语音信号盲源分离算法--fastica算法源程序，基于matlab开发环境-Speech signal blind source separation algorithm- fastica algorithm source code, matlab development environment based on
FastICA
- Fast ICA 语音信号盲源分离代码-Fast ICA
YGBSS
- 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.)
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
ICADemo
- 在盲源的情况下求解输入信号，我感觉非常有用哦(get the signal of the input)
EASI
- 用于对信号的盲源分离处理当中，将两混合信号分开。(In the blind source separation processing of a signal, the two mixed signals are separated.)
盲源信号程序
- 盲源信号程序 可以实现盲源信号分离 可直接运行(Blind source signal yyyyyyyyyyyyyyyy)
盲源分离
- 盲源分离来实现混合语音的分离，对于学习语音信号的有着很好的参考作用(Blind Source Separation (BSS) is a good reference for learning speech signals.)
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 orthogonal, that is, when the sup
GetMixMatrixUsingFCM
- 欠定盲源分离是典型的信号处理问题，最早起源于鸡尾酒问题，目前作为一类具有挑战性数学问题，本文给出了混合矩阵的一种估计方法的matlab(Underdetermined blind source separation is a typical signal processing problem, which originated from cocktail problem. At present, as a kind of challenging mathematical problem, thi