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matlab仿真模型，适用于风机发电的直流和柔性直流输电(matlab simulation model for DC fan power and flexibility of HVDC)

说明：  csharp和matlab混合编程的视频教程，很不错(csharp and mixed programming matlab video tutorial, very good)

说明：  matlab_矩形检测代码 刚刚用过很实用。可以下载看看(matlab_ rectangular test code just used the very practical. You can download to see)

先进PID控制极其Matlab仿真，很实用、很详细，附有具体程序案例，是不错的初学者教材。(Advanced PID control is extremely Matlab simulation, very practical, very detailed, with program-specific case is a good beginners textbook.)

Zernike moments calculation. Two functions, one for polynomial calculation and one for moments calculation

设计一个完整的室内无线通信系统物理层传输方案，并用matlab进行仿真根据设计要求分析计算收发机结构及主要参数，提出了一个完整的MIMO-OFDM系统设计方案，得到误比特率仿真曲线。(Design of a complete indoor wireless communication system physical layer transmission scheme, and simulation using matlab design analysis and calculation according to the structure and main parameters of the transceiver, made a complete MIMO-OFDM system design, simulation curve obtained bit error rate.)

An Evolutionary Routing Protocol for Dynamic Clustering of Wireless Sensor Networks

this is the clustering matlab code, have a nice day!

《MATLAB程序设计教程》也是一本学习MATLAB编程的书籍(MATLAB programming tutorial)

小波神经网络的源程序: 1.构造的非线性函数: 位于nninit_test.m 2.直接用WNN逼近非线性:Wnn_test.m, (内部调用小波函数) 3.遗传算法优化后逼近 :GA_Wnn_test.m (内部调用遗传算法的,初始化,适应度,解码函数)-genetic algorithm optimization WNN source : 1. Construction of the nonlinear function : nninit_test.m at 2. WNN directly with nonlinear approximation : Wnn_test.m. (internal called wavelet function) 3. Genetic Algorithm optimization approach : GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions) (Wavelet neural network source code: 1. Construction of the nonlinear function: at nninit_test.m 2. Wnn the direct use of nonlinear approximation: Wnn_test.m, (internal call wavelet function) 3. Genetic algorithm optimized approximation: GA_Wnn_test. m (internal call genetic algorithms, initialization, fitness, decoding function)-genetic algorithm optimization WNN source: 1. Construction of the nonlinear function: nninit_test.m at 2. WNN directly with nonlinear approximation: Wnn_test.m. ( internal called wavelet function) 3. Genetic Algorithm optimization approach: GA_Wnn_test.m (internal called genetic algorithms, initialize, fitness and decoding functions))