Description: 模糊支持向量机与主成分分析在人脸识别中的应用-Fuzzy Support Vector Machine with Principal Component Analysis Applied on Face Recognition Platform: |
Size: 5130240 |
Author:戴欢 |
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Description: 一个用于聚类的工具箱，内有主元分析、模糊等技术的Matlab源代码和应用实例程序Demo。-One for clustering toolbox, with principal component analysis, fuzzy techniques, such as Matlab source code and application procedures for Demo. Platform: |
Size: 12288 |
Author:Xiaojun Tang |
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Description: 用于人脸识别的模糊独立成分分析+主成分分析，用模糊支持向量机进行的分类。-Fuzzy Face Recognition for independent component analysis+ principal component analysis, using fuzzy support vector machine classification. Platform: |
Size: 2030592 |
Author:戴欢 |
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Description: 用于人脸识别的主成分分析和模糊支持向量机程序，通过测试，能完成工作-Face Recognition for the principal component analysis and fuzzy support vector machine procedures, to pass the test to complete the work Platform: |
Size: 1255424 |
Author:戴欢 |
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Description: 使用Fuzzy Cluster Mean (FCM)與Principal component analysis (PCA)分類Yeast Data-Yeast data will be classified by means of Fuzzy Cluster Mean (FCM)and Principal component analysis (PCA) based on matlab. Platform: |
Size: 12288 |
Author:Peter |
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Description: 2012年全国大学生数学建模竞赛题目--葡萄酒的评价。文件中包含葡萄酒成分数据（Excel文件）、各种数据统计处理的MATLAB函数（已封装好，直接调用），包括：数据预处理、灰色预测、灰色关联度、基于熵权法的模糊综合评价、主成分分析、系统聚类、多元线性回归等程序。-Wines Evaluation from the title of 2012 National Undergraduate Mathematical ModelingContest. The file includes many MATLAB codes about statistical analysis of data.For example: Principal component analysis Grey Relational Analysis Fuzzy Comprehensive Evaluation Based on Entropy Method System Clustering Grey Prediction Multiple linear regression and so on. We can call them directly. Platform: |
Size: 154624 |
Author:charidong |
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Description: fMRI is a very popular method in which researchers and clinicians can image
human brain activity in response to given mental tasks. This book presents a comprehensive
review of the methods for computing activity maps, while providing
an intuitive and mathematical outline of how each method works. The approaches
include statistical parametric maps (SPM), hemodynamic response modeling and
deconvolution, Bayesian, Fourier and nonparametric methods. The newest activity
maps provide information on regional connectivity and include principal and
independent component analysis, crisp and fuzzy clustering, structural equation
modeling, and dynamic causal modeling. Preprocessing and experimental design
issues are discussed with references made to the software available for implementing
the various methods. Aimed at graduate students and researchers, it will appeal
to anyone with an interest Platform: |
Size: 1456128 |
Author:mohammed |
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Description: Principal component analysis of multivariate data analysis projection, Suppressed carrier type differential phase modulation, Verify recognition algorithm based on palmprint recognition undergraduate complete set of online identity. Platform: |
Size: 150528 |
Author:kungingyingsiu
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