MATLAB-for-PDEs

说明：  一片详细介绍adaboost进行目标识别的文章。采用MSTAR数据库作为数据来源，非常经典的adaboost实现(A detailed article adaboost target recognition. MSTAR database as the data source used, to achieve a very classic adaboost)

实现M=4,8 PSK星设图 M=4的PSK系统，分别取信噪比为odB、10dB和20dB，在星座图上观察接收端接收到的信号向量。(achieve M = 4,8 PSK-based map of M = 4 PSK system, the signal-to-noise were taken odB. 10dB and 20dB, in the constellation observation receiving termination received signal vector.)

Analog clock simulation in Matlab

新手学习MATLAB画图很好的例子，程序直接复制到MATLAB中就可以运行。(MATLAB drawing newcomers to learn a good example, be copied directly into MATLAB programs can run.)

包含了数值计算的绝大部分程序，依照英文可以查找级程序(Contains most of the numerical calculation procedure can find level program in accordance with English)

支持向量机回归模型，可应用于经济、金融时间序列预测！(SVM Model)

(不错的一篇文章，已被EI收录)模型预测控制（model predictive control，MPC）路径规划算法适用于三维动态环境下的无人机（un-manned aerial vehicle，UAV）路径规划；动态贝叶斯网络（dynamic Bayesian network，DBN）能够有效推理战场态势，对无人机进行威胁评估。针对威胁尾随无人机时的路径规划问题，构建 DBN 威胁评估模型，将 UAV 在战场环境中的威胁态势用威胁等级概率表示，与 MPC 路径规划算法相结合，得到基于 DBN 威胁评估的 MPC UAV 路径规划算法。通过多组仿真分析表明，在三维动态环境下，特别是威胁尾随无人机时，基于 DBN 威胁评估的 MPC无人机路径规划算法可以得到有效的无人机路径。(The model predictive control (MPC)path planning algorithm can solve the problem of dynamic unmanned aerial vehicle (UAV)path planning.Dynamic Bayesian network (DBN)is an effective tool for rea-soning and threat assessment.Considering the problem of path planning when the dynamic threat tags the UAV,the MPC path planning algorithm combined with DBN threat assessment is presented,which used the threat lever probability to describe the threat situation.A group of simulations demonstrate the efficiency of MPC three-dimensional dynamic path planning algorithm for UAV based on DBN threat assessment especially when the dynamic threat tags the UAV.)

Tutorial and multiple Simulink examples regarding the integration of m-Files into Simulink models.

matlab仿真程序，适合初学者，比较实用，可用性高。(matlab simulation program, suitable for beginners, more practical, high-availability.)

finite difference demo code