GraduateManagementAdmissionTestProbabilityTheoryan

说明：  黑莓开发大全上篇,每个黑莓开发者都必须具备的教材,第一次发布(BlackBerry Development Daquan Part, every BlackBerry developer must have the textbooks, the first time release)

Describe: Then a voice feature extraction procedures source, in addition to containing matrix and vector operations, it also includes many voice feature extraction algorithm, including : Formant (formant) extraction

包括基金的分类、如何选择基金、如何计算费用和收益、基金投资策略和技巧、基民投资安例故事、现有基金介绍等相关内容，是一本不可多得的最全面实用的基民投资指南。 (Including the Fund)

一个比较好的ppt模板，程序员汇报的时候可以使用(A good ppt templates, programmers can use when reporting)

说明：  汽车电子行业的电路设计元件选型的手册 很不错的 而且还有Demo应用(Automotive electronics industry, circuit design components of the manual is pretty good selection but also the Demo Application)

关于关联向量机应用的最新文献！ 提出了一种核主元分析(KPCA)和关联向量机(RVM)相结合的组合建模方法。KPCA-RVM采用KPCA对原始自变量进行非线性变换并提取主成分,形成特征自变量 采用RVM,对KPCA变换后的样本数据进行回归建模,并根据模型的预报能力自适应的确定参与回归的最佳特征变量个数,消除冗余信息干扰,获得强非线性表达能力且预报性能良好的模型。并将KPCA-RVM应用于PTA装置对羧基苯甲醛(4-CBA)含量的软测量建模,结果表明该方法预测精度高于PCA-RVM和RVM。(A novel modeling method integrated KPCA with RVM was proposed. The kernel primary component analysis (KPCA) was employed to identify the principal components from the nonlinear transform data of independent variables, which were regarded as character variables. Regression between character variables and dependent variables was done based on RVM, and the optimal number of the character variables was adaptively determined according to the generalization performance of the regression model. Thus, KPCA-RVM meth...)

此书是由Tom M. Mitchell所写的机器学习的中文版。(The book is written by Tom M. Mitchell machine learning of the Chinese version.)

C C++ interview Questions and Answers

this is a plc program

f16的非线性模型设计，也许对你有用。MATLAB的，里面有配套说明(Nonlinear_F16_Fighter_Model)