Description: ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2].
-ICA can be used in brain activation studies to reduce the number of dimension and filter out independent and interesting activations. This demonstration shows two studies. One provided by Hvidovre Universitets Hospital, Denmark, that consists of fMRI scannings of humans. Another provided by the EU sponsored MAPAWAMO project from fMRI scannings of monkeys. In the demo comparison between icaMS, icaML, icaMF, icaMF (positive sources) and PCA can be made. More detailes can found in [2]. Platform: |
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Author:海心 |
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Description: 基于kernel pca的非线性降维算法，原文发表于神经计算杂志上，有兴趣者可以先看论文。-PCA-based kernel of nonlinear reduced dimension algorithm, the original published in the Journal of neural computation, those interested can read papers. Platform: |
Size: 1024 |
Author:武旗 |
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Description: 做模式分类时（例如指纹识别，人脸识别），一个需要处理的难题是维数非常大，人脸往往是百万维的，目前计算机的能力还不足以快速地计算这么高维的数据。pca是一中降维的方法，用它可以把高维数据映射到一个维数较低的空间上考虑。-To do pattern classification (for example, fingerprint identification, face recognition), a need to deal with the problem is very large dimension, often millions of people face-dimensional, the current capacity of the computer fast enough to calculate such a high-dimensional data. PCA is a dimensionality reduction of the method, it can be high dimensional data is mapped to a lower dimension space to consider. Platform: |
Size: 1024 |
Author:李志焕 |
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Description: 用matlab实现的pca算法，用于将维，适用于各种试验，如人脸识别程序-Using matlab realize the PCA algorithm is used to dimension, applicable to a variety of tests, procedures such as face recognition Platform: |
Size: 631808 |
Author:钱靖 |
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Description: 在MATLAB上所使用的PCA程序，主要應用於過濾相對較不重要的特徵值(dimension)，例如在三度空間的某些點具有(x,y,z)值，因為這些點有共同的一個持徵，就是z值相對於x,y值來得小很多(不明顯)，所以就以X,Y軸來表示這些點。此時就達成去除掉z的特徵值(dimension)。
-MATLAB used in the PCA procedure, mainly used in filtering relatively unimportant eigenvalue (dimension), for example, in some points with three-dimensional (x, y, z) values, because these points have a common one sign holders, that is, z values compared with the x, y values much smaller than (not obvious), so on to X, Y axis to express these points. Reached at this time to get rid of z eigenvalues (dimension). Platform: |
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Author:iceryu01 |
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Description: This toolbox is an educational and recreative toolbox around recent ideas in the field of dimension reduction.
* PCA : classical Principal Componnent Analysis (linear projection).
* Nonlinear dimensionality reduction by locally linear embedding.
* Laplacian Eigenmaps for dimensionality reduction and data representation-This toolbox is an educational and recreative toolbox around recent ideas in the field of dimension reduction.
* PCA : classical Principal Componnent Analysis (linear projection).
* Nonlinear dimensionality reduction by locally linear embedding.
* Laplacian Eigenmaps for dimensionality reduction and data representation Platform: |
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Author:tra ba huy |
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Description: 元胞自动机的虚拟程序
开发工具：Microsoft Visual Basic 6.0
运行平台：Windows OS
(VB编译，代码未优化,运行速度较慢)
词语解释：
CA，cellular automata，元胞自动机，或称细胞自动机。
模式(Pattern)，多个细胞构成的一个状态组合。
模型：
维度，二维四方网格
细胞，两种状态（活、死）；一个方格代表一个细胞。
邻居，Moore型(上、下、左、右、左上、右上、左下、右下)
规则，1)一个活着的细胞如果保持活的状态，那么它必需具有2至3个活的邻居，否则它就变成死的状态。2)一个死的细胞如果变成活的，那么它必需恰好有3个活的邻居。
程序功能：
1. 方格水平数量和垂直数量自由设置(最少为2，即2*2的网格)
2. 随机初始化细胞（细胞为活的概率可设置）
3. CA状态的演化，可自动逐步也可手动逐步。
4. 两种显示模式（用于研究可能的规律）
5. 可对CA状态进行编辑（操作类似简单的绘图）。
6. 模式。可以选择局部网格为模式；模式可以被旋转和翻转操作；模式可以被保存到文件和插入到网格。
7. 可以保存当前CA的状态到文件，也可载入已保存的CA状态。-Cellular Automata virtual procedure
Development tools: Microsoft Visual Basic 6.0
Platform: Windows OS
(VB compiler, the code is not optimized to run more slowly)
Words to explain:
CA, cellular automata, cellular automaton, or cellular automata.
Pattern (Pattern), consisting of a number of cells in a state of combination.
Model:
Dimension, two-dimensional grid Quartet
Cells, two states (living and dead) a grid on behalf of a cell.
Neighbors, Moore-type (upper and lower, left, right, left, right, left, bottom right)
Rules, 1) If a living cell to maintain a state of living, then it must have 2-3 living neighbors, otherwise it becomes a state of death. 2) If a dead cell becomes live, then it must have exactly three live neighbors.
Program features:
1. The number of grid levels and the number of free vertical settings (at least 2, which is 2* 2 grid)
2. Random initialization cells (the probability Platform: |
Size: 106496 |
Author:iDo4LT |
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Description: PCA+LDA人脸识别，识别率高于单独PCA或LDA算法。需要matlab dimension reducation toolbox。-Face verification using PCA and LDA fusion. Better performance than single PCA or LDA algorithm. The image database is included. Matlab dimension reduction toolbox is requrired. Platform: |
Size: 1975296 |
Author:taiji |
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Description: 该工具箱中包含了多种降维算法。其中有传统的PCA和Local PCA算法，也有典型的流形学习算法，如Isomap、LLE、HLLE、Laplacian Eigenmaps 和 Local Tangent Space 。-The toolbox contains a variety of dimensionality reduction algorithms. In which the traditional PCA and Local PCA algorithms, there are the typical manifold learning algorithms such as Isomap, LLE, HLLE, Laplacian Eigenmaps and Local Tangent Space. Platform: |
Size: 195584 |
Author:芝麻 |
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Description: pca特征向量提取 利用pca的方法获取特征植及特征向量 最后可以自己根据需要降维-pca pca feature vector extraction method using characteristics of plants and to obtain the final feature vector dimension reduction can be their own as needed Platform: |
Size: 4096 |
Author:张天号 |
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Description: 模式识别作业-完全自编仿真程序。先用PCA对IRIS数据集进行降维，然后用最小错误法对降维的数据进行分类。压缩包中既包括matlab源代码，又有自己写的报告，还有.MAT格式的IRIS数据集用作程序调用。程序有详细注释，很容易懂。最后结果输出到txt文件中。-Pattern recognition operations- completely self simulation program. First on the IRIS data set with PCA dimension reduction, and then with the minimum error method to classify the data dimension reduction. Both compressed package matlab source code, but also write their own reports, as well. MAT format, the program calls for IRIS data set. Procedures detailed notes, it is easy to understand. Finally, the output to a txt file.
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Author:yumingwei |
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Description: K-Means算法,不要求建立模型之后对结果进行新的预测，没有相应的标签，只是根据数据的特征对数据进行聚类。主成分分析降维对数据进行可视化操作,对features进行降维.(K-Means algorithm does not require the establishment of the model after the new prediction of the results, there is no corresponding tag, but only on the characteristics of data clustering data. The principal component analysis reduces the dimension, carries on the visualization operation to the data, reduces the dimension to the features.) Platform: |
Size: 33792 |
Author:赵嘉慧
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Description: 使用matlab自带的函数princomp()计算主成分，当维数很高时通常会出现内存耗尽的错误，即使内存足够也非常耗时。快速pca能加快计算进程且减小内存占用，更容易计算较大尺寸的图像主成分。(Use MATLAB's own function princomp () to calculate the principal component. When the dimension is very high, the memory exhaustion error usually occurs, even if the memory is enough, it is very time-consuming. Fast PCA can speed up the computation process and reduce memory footprint, making it easier to calculate the larger image principal components.) Platform: |
Size: 316416 |
Author:sdpscnc |
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Description: 先通过图像处理提取人脸的各个特征，然后对人脸通过PCA进行降维，然后通过SVM进行人脸识别(Firstly, the features of human face are extracted by image processing, then the dimension of human face is reduced by PCA, and then the face is recognized by SVM) Platform: |
Size: 9374720 |
Author:有始有终 |
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Description: 应用于数据降维的一种MATLAB程序，可以实现从高维到低维的降解(A matlab program applied to data dimensionality reduction can realize the degradation from high dimension to low dimension) Platform: |
Size: 1024 |
Author:lzkzgy |
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Description: 该课题为基于MATLAB平台的PCA的人脸识别系统。原理为：从一副生活照中寻找到人脸，分割人脸区域图像，PCA算法进行降维，和库里图片进行对比，输出目标人脸以及相关个人信息。该课题还可以继续二次开发，做成库内外人脸的识别，如果是库外人脸则实现报警等。(This project is a PCA face recognition system based on MATLAB platform. The principle is: find the face from a life photo, segment the face image, reduce the dimension of PCA algorithm, compare with the library image, output the target face and relevant personal information. The subject can also continue the secondary development to make face recognition inside and outside the library. If it is a face outside the library, alarm will be realized.) Platform: |
Size: 13575168 |
Author:可乐一生 |
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