ASK_FSK_PSK

matlab中矢量控制模型，其中32变换可以用S函数来实现(matlab in vector control model, of which 32 can transform S function to realize)

说明：  对高斯光束在不同位置的光强分布进行模拟仿真，主要是光腰和焦点位置(The intensity distribution of Gaussian beam in different positions is simulated, mainly in the waist and focus position)

涵盖了完整的SVM程序代码，唯一缺憾没有代码解释，分享了。。。(SVM covering the complete code, the only shortcoming is no code interpreter, shared. . .)

learning robot implementation

粒子群算法的Matlab程序，用于多目标优化极值的计算(Particle swarm optimization Matlab program for calculation of extreme multi-objective optimization)

是一本Matlab方面入门的好教材，是初学者的最佳选择(Matlab is a good material for aspects of entry is the best choice for beginners)

说明：  具体什么内容，自己看了就知道了，学到的用了才是最好的，否则不看也罢(What is the specific content of their reading will know, learn to use the best, otherwise do not look worth mentioning)

扩频通信系统仿真 ——系统将基带信号（即信息）的频谱扩展至很宽的频带上，然后再进行传输，即将欲传输的信息数据用伪随机序列编码调制，实现频谱扩展，然后通过信道编码发送出去；接收端采用与发送端完全相同的伪随机序列作为本地解扩信号进行相关处理，以恢复信息，最后进行解调，完成整个系统的接收。(Simulation of spread spectrum communication system- the system baseband signal (ie, information) be extended to a wide spectrum of frequency bands, and then transferred, will want to use transmitted information data sequence of pseudo-random code modulation, to achieve expansion of the spectrum, and then sent channel coding receiver and transmitter use the same pseudo-random sequence as related to the local despreading signal processing, in order to restore the information, the final demodulation, the receiver to complete the system.)

有限差分法中简单迭代法计算场域节点的应用(Finite difference method in a simple iterative method to calculate the application node)

一个关于matlab优化工具箱GOT中的遗传算法函数（GA）和全局优化算法函数（Globalsearch）优化能力的小对比，前者寻优快，但是结果不稳定，在风电场协同有功出力优化上面甚至可能比不过传统的单个风机层面的优化。后者计算量大，耗时较长，但是每次计算结果稳定，较传统单台风机层面优化有少量的提升。Tips:1,本文风场的建模只是采用了PARK模型，实际风场的气动过程应该还要复杂一些，未经实际风场验证，权当是工程优化入门 2,单个风机层面的功率系数Cp参数来源于NREL 5MW模型，跟实际叶片气动性能有关，可靠性未知。3,这种风场级别的协同优化主要考虑尾流因而更加适用于地形较平坦的风电场。《基于风机运行参数协同设定的风电场有功出力优化》是部分由这个程序支撑的，欢迎交流。(The classical operation strategy of a wind farm works with a principle that each wind turbine converting as much aerodynamic power as available the incoming airflow. But this does not guarantee that the power converted by the whole wind farm be a maximum due to the wake effect. Unlike the conventional operation, this paper proposes the collaborative setting of the operation point of each turbine so that the overall production of the wind farm is maximized. The optimization is performed by Matlab Global Optimization Toolbox(GOT) based on a PARK wake model accompany with the area-weighted quadratic sum method. The strategy was proved applicable in many cases by sensitivity analysis. As an important side effect, the proposed method also allows decreasing the added turbulence, hence the mechanical load produced by wakes. As a consequence, the overall wind farm availability is increased. )