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- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之七十二-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
1
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之七十一-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
2
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之七十-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate is
3
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之六十九-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
4
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之六十八-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
5
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之六十七-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
6
- The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate is sixty-seven perce-The program use pca, kpca, SVM, PLS, fisher, bayesian r
1
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之六十-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate is
2
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之五十九-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
3
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之五十八-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
4
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之五十七-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
5
- 本程序用pca，kpca,svm,pls,fisher，贝叶斯实现cstr和csth过程的故障检诊断，诊断率为百分之九十九，故障识别率为百分之五十六-The program use pca, kpca, SVM, PLS, fisher, bayesian realize CSTR and CSTH process for diagnosis fault diagnosis rate is ninety-nine percent, and the fault recognition rate i
pcaForSVM
- 关于SVM数据预处理的函数，降低维数的PCA函数-The function of data pretreatment on SVM, reduce dimension of PCA function
pcaForSVM
- 支持向量机（SVM）主成分分析法进行预处理筛选变量- support vector machine (SVM)，PCA(principal component analysis)
face-recognition
- 一个有关人脸识别的程序，是PCA和SVM的，可以运行-a code about face recognition
pq_pcasvm
- 使用小波能量差提取信号，PCA降维，SVM对电能质量扰动分类。-Extract the signal using the wavelet energy difference between the PCA dimensionality reduction, SVM classification of power quality disturbances.
chapter13
- matlab实现PCA和SVM人脸识别 主成分分析 和 支持向量机-the matlab realize PCA and SVM face recognition
stprtool
- 统计模式识别，包括PCA LDA SVM-Statistical pattern recognition, including the PCA LDA SVM
svm_matlab_facerecognition
- 利用PCA算法进行特征提取和数据降维，再用SVM算法进行人脸识别的程序，里面有人脸数据库！-Use PCA algorithm for feature extraction and data reduction, and then SVM algorithm recognition program, which was face !
ckxqwsdj
- 通过反复训练模板能有较高的识别率，zFzySva参数现代信号处理中谱估计在matlab中的使用，对于初学者具有参考意义，结合PCA的尺度不变特征变换(SIFT)算法，EyFKrQV条件包括最小二乘法、SVM、神经网络、1_k近邻法,具有丰富的参数选项。- Through repeated training zFzySvalate have higher recognition rate, zFzySva parameter Modern signal processing used in th