搜索资源列表
ICA
- 辛苦收集的关于独立成分分析的ppt文档，可帮助你快速了解主成分分析的主要内容及发展-Hard to collect on the independent component analysis of ppt documents, can help you quickly understand the principal component analysis and development of the main content
KernelBasedObjectTracking
- A new approach toward target representation and localization, the central component in visual tracking of nonrigid objects, is proposed. The feature histogram-based target representations are regularized by spatial masking with an isotropic kernel.
apublier
- The multipath performance of a given signal/receiver combination depends on various signal and receiver parameters like signal type/modulation scheme pre correlation bandwidth and filter characteristics, chipping rate of code ,relative power levels o
FastICA_21
- 快速独立分量变换，可用于信号特征的提取以及端点检测等，非常好用！-Fast independent component transform, can be used for the extraction of signal characteristics, such as endpoint detection, as well as very easy to use!
kernel-ica1_1
- 基于核函数的主分量分析法源代码，可用于人脸识别-Kernel-based principal component analysis source code, can be used for face recognition
AMUSE
- AMUSE，独立成分分析(ICA)算法之一，用于混合语音信号的盲分离-AMUSE, algorithm of independent component analysis, used in blind speech signal separation.
IcaComonMatlab.tar
- 独立成分分析是近年来出现的一种强有力的数据分析工具。1994年由Comon给出了ICA的一个较为严格的数学定义，其思想最早是由Heranlt和Jutten于1986年提出来的。ICA从出现到现在虽然时间不长，然而无论从理论上还是应用上，它正受到越来越多的关注，成为国内外研究的一个热点。特别是从应用角度看，它的应用领域与应用前景都是非常广阔的，目前主要应用于盲源分离、图像处理、语言识别、通信、生物医学信号处理、脑功能成像研究、故障诊断、特征提取、金融时间序列分析和数据挖掘等。 IC
KPCA
- Kernel Principal Component Analysis
PCA-SIFT
- 共享主成份尺度不变变换PCA-SIFT代码，用于SAR图像配准，希望对各位雷达爱好者和SAR工作者有用！-Principle component analysis, PCA- Scale invariant feature transform-SIFT used for SAR processing.
kernel-ica1_2
- 核独立分量分析，一种基于核函数的独立分量分析方法-Kernel Independent Component Analysis, a Kernel-based Independent Component Analysis! !
MATLAB_Medical_Image_Process_Experiments
- MATLAB医学影像处理实验(内含14个原代码及教学的说明) (1)Plot a sine function using MATLAB, and write the data into a file (2)Read data from a file, plot a SINC function, and append the result back to the same file (3)Plot a Gaussian distribution using MATLAB (4)Fo
KPCA_p
- 核主成分分析中使用多项式核函数时的MATLAB代码，有注释，易看懂。-Kernel Principal Component Analysis in the use of polynomial kernel function of the MATLAB code, annotated, easy read.
MPCASourceCode
- The matlab codes provided here implement two algorithms multilinear principal component analysis to run the face recognition using FERET database.
matlab_v
- Motion Tracking === === === This tarball contains all code required to run the tracking algorithm on a sequence of images. Run the file run_tracker.m in Matlab and follow the instructions. You will need to have a directory of sequentiall
PCA
- 主成分分析代码，用matlab实现的，请大家参阅。-Principal component analysis code, matlab implementation, please refer to the.
pca
- pca分类算法，3个参数，一个是样本数据x，另外一个是主成分累积贡献率的一个闸值，作为选定主成分个数的一个重要数据。-pca classification algorithm, three parameters, one is the sample data x, the other is the main component of the cumulative contribution rate of the value of a gate, as the number of selected
normalise
- Normalises image values to 0-1, or to desired mean and variance Usage: n = normalise(im) Offsets and rescales image so that the minimum value is 0 and the maximum value is 1. Result is returned in n. If the image is colour the
P-svWaveFieldSimulationConversion
- 二层地质模型波场模拟,用有限差分进行波场的模拟,充分利用多波多分量地震记录，以及各向异性方面的独特信息，可有效地减少 纵波勘探的多解性，定量地描述裂缝储层，改善某些纵波资料成像不好地区的构造 成像。这样可获得比纵波分辨率高的多波剖面，从而有利于研究小幅度构造、断层、 裂缝裂隙等复杂地质现象，对油气勘探与开发具有现实意义和实用价值-Two-layer geological model wave field simulation, using finite difference wave
emd
- 经验模式分解(EMD)将信号分解成多个IMF分量，每个IMF分量代表一定频率尺度的模式完整源代码-Empirical Mode Decomposition (EMD) to decompose the signal into a number of IMF components, each component of IMF on behalf of a certain frequency-scale model of the full source code
ode45
- 解常微分方程的Matlab程序 字符串ypfun是用以表示f(t, y)的M文件名, tspan=[t0, tfinal]表示自变量初值t0和终值tf y0表示初值向量y0，可选参数options为用odeset设置精度等参数。 输出列向量tout表示节点，输出矩阵yout 表示数值解，每一列对应y的一个分量。若无输出参数，则作出图形。-Solution of ordinary differential equations of the Matlab program is