kalman

用matlab实现支持向量机分类算法，通过对数据进行测试训练来进行分类(Using matlab implementation support to the classification algorithms to data, through testing and training to categorize )

说明：  ％ PURPOSE : Demonstrate the differences between the following filters on the same problem: ％ ％ 1) Extended Kalman Filter (EKF) ％ 2) Unscented Kalman Filter (UKF) ％ 3) Particle Filter (PF) ％ 4) PF with EKF proposal (PFEKF) ％ 5) PF with UKF proposal (PFUKF)( PURPOSE: Demonstrate the differences between the following filters on the same problem: 1) Extended Kalman Filter (EKF) 2) Unscented Kalman Filter (UKF) 3) Particle Filter (PF) 4) PF with EKF proposal ( PFEKF) 5) PF with UKF proposal (PFUKF))

说明：  多变量寻优的源码，包括基本算法如下：DFP法（又称变尺度法），BFS法、一阶梯度法，共扼梯度法。(multivariate optimization of the source code, including basic algorithm is as follows : DFP Act (also known as the variable scale), BFS, a ladder degrees, a total of the accused gradient method.)

FACS表情图释，包括肌肉图解和各种表情的诠释，有助于人脸表情识别研究学习(FACS expression emoticons, including muscle illustrations and expressive interpretation, contribute to the study of facial expression recognition learning)

PID generator controler

分类工具包，含有多个分类算法的matlab源程序，适用于类别数据的分类和可视化(The Classification toolbox for MATLAB is a collection of MATLAB modules for calculating classification (supervised pattern recognition) multivariate models: Discriminant Analysis, Partial Least Square Discriminant Analysis (PLSDA), Classification trees (CART), K-Nearest Neighbors (kNN) and Soft Independent Modeling of Class Analogy (SIMCA). This is the version 3.1 of the Classification toolbox for MATLAB Classification toolbox for MATLAB has been released by Milano Chemometrics and QSAR research Group. Visit our website at www.disat.unimib.it/chm )

matlab 有限元结构动力学与工程应用 第二章(The second chapter of the matlab finite element structural dynamics and engineering applications)

Sampling matlab source

经典的Gabor滤波器的源码，Matlab实现(Gabor Filter code in Matlab)

这是另个对磨床加工工件工序问题建模求解的MATLAB程序，方法合理可靠(This is another one of the workpiece grinding process modeling and solving the problem of the MATLAB program, the method is reasonable and reliable)