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初学者可以参考一下 作为MATLAB的入门教程与实践(Beginners can refer to as the entry MATLAB Tutorial and Practice)

经典的扩展卡尔曼滤波卡尔曼滤波程序，首先对非线性函数取一阶近似，生成近似的新型函数，然后进行卡尔曼滤波，通过一步状态和估协方差估计产生新息，然后生成状态预测(Classical extended Kalman filter, Kalman filter procedure, first take the first order approximation of nonlinear function to generate the new function approximation, and then proceed to the Kalman filter step state estimate covariance is estimated to generate new interest, and then generate the state prediction)

压缩感知的信号恢复算法集合，包括ISD_v1.1，l1magic-1.1和sparsify_0_5(Compressed sensing signal recovery algorithms collections, including ISD_v1.1, l1magic-1.1 and sparsify_0_5)

Lambert制导问题的优化算法，通过改变初值的计算方法减少了一半以上的运算量。(Optimization of Lambert Guidance problem )

说明：  实现指纹识别的功能。图像的预处理、指纹特征提取、指纹匹配。(Realize the function of fingerprint identification. Image preprocessing, fingerprint feature extraction, fingerprint matching.)

VC MATLAB 混编示例 ppWizard has created this matlab调用 application for you. This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application. This file contains a summary of what you will find in each of the files that make up your matlab调用 application.(ppWizard has created this matlab调用 application for you. This application not only demonstrates the basics of using the Microsoft Foundation classes but is also a starting point for writing your application. This file contains a summary of what you will find in each of the files that make up your matlab调用 application.)

说明：  自适应交互式多模型滤波程序，内附详细说明(Interactive multiple model adaptive filtering process, containing details)

Unmanned Wireless Sensor Network

说明：  对人体的图像序列进行unscented kalman filter 追踪，参考最经典的UKF算法编写，是学习UKF算法的比较入门的程序(Image sequences on the human body, unscented kalman filter for tracking, the most classical reference to the preparation of the UKF algorithm is a learning algorithm UKF procedure entry )

基于白噪声法路面不平度仿真程序，可以仿真得到路面不平度的时域激励。(Method based on white noise process simulation of road roughness, road roughness can be simulated by time-domain excitation.)