quadrotorcontrol

说明：  rbf源码说明有例子，有详细解说，说明步骤和原理。希望对大家有用(有例子，有详细解说，说明步骤和原理。希望对大家有用)

通信原理课程设计，对信号进行量化编码，计算SQNR信号量化噪声比，信号功率，量化噪声功率信号量化噪声比 (Communication theory curriculum design, signal quantization coding to calculate the SQNR signal quantization noise ratio, signal power, the quantization noise power signal to quantization noise ratio)

基于matlab编写了SQP法，乘子法，共轭梯度法，拟牛顿法，信赖域法，最速下降法与牛顿法的最新程序，功能很强大，可供编程参考。(Based on the preparation of MATLAB SQP, multiplier method, conjugate gradient method, quasi-Newton method, trust region method, steepest descent method with the Newton-Raphson method the latest procedures, functions very powerful, can be used for programming reference.)

GSM中GMSK调制信号的产生，这是一个好用的频偏估计算法的matlab仿真程序,迭代自组织数据分析。( GSM is GMSK modulation signal generation, This is a useful frequency estimation algorithm matlab simulation program, Iterative self-organizing data analysis.)

使用MATLAB进行故障诊断与使用vb进行仿真校正~~里面提供了需要的数据库与数据，不好意思语句解释很少~~小弟也是初学者(Fault diagnosis using the MATLAB simulation corrected with the use of vb ~ ~ which provides the necessary databases and data, I am sorry statement to explain few ~ ~ little brother is also a beginner)

完整的Matlab程序，本程序为人工鱼群算法优化支持向量机参数，并取得良好效果(Complete Matlab program, the procedure for the artificial fish school algorithm parameters optimized support vector machine, and achieved good results)

说明：  计算Diebold and Yilmaz(2014)溢出指数 Diebold F X, Yilmaz K. Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 2012, 28(1): 57-66.(Diebold and Yilmaz(2014) spillover index Diebold F X, Yilmaz K. Better to give than to receive: Predictive directional measurement of volatility spillovers. International Journal of Forecasting, 2012, 28(1): 57-66.)

说明：  自己做的基于MATLAB的dsb编码，已经通过了调试(Do their own code based on MATLAB of dsb has been adopted debugging)

频率域扫描建模，可以匹配传递函数，很实用的仿真。(Scanning frequency domain model, can match the transfer function, it is useful simulation.)

对一幅图像实现不同角度的旋转，从而可以观察不同角度的结果。( rotate_image- rotates an image given inside a matrix by the amount of "degree" counter-clockwise using linear interpolation of the output grid points from the back-rotated input points in this way, the output image will never have a "blank" point)