Description: A full implementation of ICA,PCA,LDA,SVM,in both orginal and incremental in model of real time learnign for face recognition. Platform: |
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Author:dasf |
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Description: 盲源分离FastICA、matalab程序，-FAST KERNEL ICA |
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Version 1.0- February 2007
Copyright 2007 Stefanie Jegelka, Hao Shen, Arthur Gretton
This package contains a Matlab implementation of the Fast Kernel ICA
algorithm as described in [1].
Kernel ICA is based on minimizing a kernel measure of statistical
independence, namely the Hilbert-Schmidt norm of the covariance
operator in feature space (see [3]: this is called HSIC). Given an (n
x m) matrix W of n samples from m mixed sources, the goal is to find a
demixing matrix X such that the dependence between the estimated
unmixed sources X *W is minimal. FastKICA uses an approximate Newton
method to perfom this optimization. For more information on the
algorithm, read [1], and for more information on HSIC, refer to [3].
The functions chol_gauss and amariD are taken from and based on,
respectively, code from Francis Bach (available at
http://cmm.ensmp.fr/~bach/kernel-ica/index.htm). The derivative is
com Platform: |
Size: 97280 |
Author:wanghqiang |
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Description: 基于matlab的PCA人脸识别完成程序，包含特征值与特征向量的提取、训练样本以复制到matlab即可，成功运行，及最后的识别检验-A full implementation of ICA,PCA,LDA,SVM,in both orginal and incremental in model of real time learnign for face recognition Platform: |
Size: 1024 |
Author:zhaolei |
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Description: 独立成分分析ICA利用MATLAB实现。可以运行，简单易懂，方便学习-Independent component analysis ICA using MATLAB implementation. You can run, easy to understand, easy to learn Platform: |
Size: 486400 |
Author:hb |
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Description: DC-DC部分采用定功率单环控制，利用matlab GUI实现的串口编程例子，实现了对10个数字音的识别，用于时频分析算法，FIR 底通和带通滤波器和IIR 底通和带通滤波器，ICA（主分量分析）算法和程序，BP神经网络用于函数拟合与模式识别，插值与拟合，解方程，数据分析。- DC-DC power single-part set-loop control, Use serial programming examples matlab GUI implementation, To achieve the recognition of 10 digital sound, For time-frequency analysis algorithm, Bottom-pass and band-pass FIR and IIR filter bottom pass and band-pass filter, ICA (Principal Component Analysis) algorithm and procedures, BP neural network function fitting and pattern recognition, Interpolation and fitting, solution of equations, data analysis. Platform: |
Size: 5120 |
Author:tkawtiug |
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Description: ICA（主分量分析）算法和程序，均值便宜跟踪的示例，三相光伏逆变并网的仿真，仿真效率很高的，用于时频分析算法，给出接收信号眼图及系统仿真误码率，利用matlab GUI实现的串口编程例子，使用大量的有限元法求解偏微分方程。- ICA (Principal Component Analysis) algorithm and procedures, Example tracking mean cheap, Three-phase photovoltaic inverter and network simulation, High simulation efficiency, For time-frequency analysis algorithm, The received signal is given eye and BER simulation systems, Use serial programming examples matlab GUI implementation, Using a large number of finite element method to solve partial differential equations. Platform: |
Size: 10240 |
Author:tahuzcug |
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Description: 相关分析过程的matlab方法，时间序列数据分析中的梅林变换工具，有小波分析的盲信号处理，均值便宜跟踪的示例，使用高阶累积量对MPSK信号进行调制识别，包括调制，解调，信噪比计算，利用matlab GUI实现的串口编程例子，ICA（主分量分析）算法和程序。- Correlation analysis process matlab method, Time series data analysis Mellin transform tool, There Wavelet Analysis Blind Signal Processing, Example tracking mean cheap, Using high-order cumulants of MPSK signal modulation recognition, Includes the modulation, demodulation, signal to noise ratio calculation, Use serial programming examples matlab GUI implementation, ICA (Principal Component Analysis) algorithm and procedures. Platform: |
Size: 5120 |
Author:hucfp |
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Description: 仿真效果非常好，插值与拟合的matlab实现，ICA（主分量分析）算法和程序。- Simulation of the effect is very good, Interpolation and fitting matlab implementation, ICA (Principal Component Analysis) algorithm and procedures. Platform: |
Size: 9216 |
Author:樊增梅 |
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Description: 殖民竞争算法代码（CCA）也被称为帝国主义的竞争算法（ICA），这是其在matlab中的实现。
-Colonial competitive algorithm codes (CCA) is also known as imperialist competitive algorithm (ICA), which is in its implementation in matlab. Platform: |
Size: 16384 |
Author:snjun |
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Description: ICA (Principal Component Analysis) algorithm and procedures, Use serial programming examples matlab GUI implementation, Can realize the two-dimensional data clustering. Platform: |
Size: 149504 |
Author:funfaifaosai
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