Description: 用主成分分析与神经网络进行人脸的识别
文件是整个的MATLAB数据文件-using principal component analysis and neural networks face identification document is the entire data file MATLAB Platform: |
Size: 32768 |
Author: |
Hits:
Description: 基于神经元网络和 Linear Auto-Associative memory 和pca的人脸识别程序。-based on neural network and Linear Auto-Associative memory pca and face recognition procedures. Platform: |
Size: 5120 |
Author:王大宝 |
Hits:
Description: 利用主成分分析法对BP神经网络的输入参数进行降维,然后进行网络的训练,PCA-BP处理的结果同单一的bp相比,不仅提高了网络的收敛速度,而且提高了网络对预测数据分类的精度-Using principal component analysis method of BP neural network for dimensionality reduction of input parameters, and then training the network, PCA-BP deal with the results of a single bp, compared with not only improve the network convergence rate, and improve the network prediction data Classification accuracy Platform: |
Size: 1024 |
Author:娜娜 |
Hits:
Description: 基于PCA和神经网络的人脸识别方法研究方面的资料,希望对你们有帮助-PCA and neural network-based face recognition method of information, in the hope that you have to help Platform: |
Size: 268288 |
Author:lidandan |
Hits:
Description: 一个外国人写的人脸检测程序,用到svm,pca,神经网络,还不错-Written by a foreigner face detection procedure, used svm, pca, neural network, but also good Platform: |
Size: 194560 |
Author:谢朝 |
Hits:
Description: 神经网络PCA的基本结构
PCA的基本原理
PCA算法的进一步扩展
研究网络遇到的问题
PCA仿真应用
-PCA neural network basic structure of the basic principles of PCA algorithm PCA further expansion of research networks simulation problems encountered by the application of PCA Platform: |
Size: 145408 |
Author:肖恒辉 |
Hits:
Description: 将pca和elman神经网络结合起来,找到了主要的变量-The PCA and the Elman neural network to combine to find the main variables Platform: |
Size: 1024 |
Author:王娆芬 |
Hits:
Description: 用基于Oja准则的PCA神经网络方法实现MUSIC算法,完成DOA估计 -Oja-based guidelines for the PCA neural network method MUSIC algorithm, the completion of the estimated DOA Platform: |
Size: 2048 |
Author:金江 |
Hits:
Description: (压缩包里一共有5个代码)
pca+lda+粗糙集+模糊神经网络
saveORLimage.m将ORL人脸库分为测试集ptest和训练集pstudy存为imagedata.mat
1.savelda.m将人脸库先进行pca降维,再用lda进行特征提取,得到新的测试集ldatest和训练集ldastudy存为imageldadata.mat
2.对ldastudy进行离散化(discretimage.m),得到离散化矩阵disdata,存入到imagedisdata.mat
3.将disdata组成决策表(savers.m),通过对disdata的条件属性进行约简,得到其一个约简,组成新的测试集rstest和训练集rsstudy存为imagersdata.mat
4.对rsstudy进行模糊神经网络训练(savecul.m),对模糊神经网络的参数进行调整学习将其存入culdata.mat
5.用runfnn.m对rstest进行测试得到其识别率
savem.m和cm.m是用最小距离分类器对训练集和测试集进行分类.-pca+ lda+ Rough Set+ fuzzy neural network
saveORLimage.m will ORL face database is divided into test set and training set ptest for pstudy keep imagedata.mat
Treasury will face 1.savelda.m first dimensionality reduction pca, lda used feature extraction, a new test set and training set ldatest for ldastudy keep imageldadata.mat
2. Ldastudy carried out on the discretization (discretimage.m), to be discrete matrix of disdata, deposited to imagedisdata.mat
3. Disdata the composition of the decision table (savers.m), the conditions on the attributes disdata about Jane, has been one of its reduction to form the new test set and training set rstest for rsstudy keep imagersdata.mat
4. Rsstudy training fuzzy neural network (savecul.m), on the parameters of fuzzy neural network to learn to adjust their deposit culdata.mat
5. Rstest used to test for runfnn.m by its recognition rate
cm.m is savem.m and minimum distance classifier on the training set and test set classificati Platform: |
Size: 2048 |
Author:dong |
Hits:
Description: This folder contains the following sub-folders which are essential in our project:
1.Raw Data
All the raw data collected from Flagstaff hill, CMU Athletic Field, and Railroad on Neville St.
2.Filter
Filter to rule out signal of Channel 1 and Channel 6
3.SVM_quadratic kernel_39
SVM code with quadratic kernel
4.PCA+KNN_62 :
PCA+KNN code
5.PCA+SVM_polynomial Kernel_50
PCA+SVM code with polynomial kernel
6.ANN
Artificial Neural Network code
7.PlotTerrain
Project demo video with actual result -This folder contains the following sub-folders which are essential in our project:
1.Raw Data
All the raw data collected from Flagstaff hill, CMU Athletic Field, and Railroad on Neville St.
2.Filter
Filter to rule out signal of Channel 1 and Channel 6
3.SVM_quadratic kernel_39
SVM code with quadratic kernel
4.PCA+KNN_62 :
PCA+KNN code
5.PCA+SVM_polynomial Kernel_50
PCA+SVM code with polynomial kernel
6.ANN
Artificial Neural Network code
7.PlotTerrain
Project demo video with actual result
Platform: |
Size: 3803136 |
Author:Chao |
Hits: