NCO_sine_gen

线性卷积和循环卷积的matlab生成，源程序为此(Linear convolution and circular convolution matlab generate, source code)

数字信号处理 应用MATLAB 中文pdf(Digital signal processing applications MATLAB Chinese pdf)

智能优化算法标准测试函数，cec09动态问题测试函数(Benchmark Generator for CEC 2009 Competition on Dynamic Optimization)

应用matlab绘制各样投影的地图，以及相关的图形绘制等等等(plot the map with matlab, that is a very useful tool)

编写了龙格现象中举例的函数（1/（1+x^2））的三次样条插值图像和原图像的比较，此程序简单适用。(Prepared Runge phenomenon, for example a function of (1/(1+ X ^ 2)) of cubic spline interpolation image and the original image compared to a simple application of this procedure.)

AMI编码功能函数， (AMI encoding function)

用于对全景镜头进行标定，能求解出图像上对应点的世界坐标的方向向量(The OcamCalib Toolbox for Matlab allows the user (also inexpert users) to calibrate any central omnidirectional camera, that is, any panoramic camera having a single effective viewpoint (see section 17). The Toolbox implements the procedure initially described in the paper(Scaramuzza, D., Martinelli, A. and Siegwart, R., (2006). "A Flexible Technique for Accurate Omnidirectional Camera Calibration and Structure from Motion", Proceedings of IEEE International Conference of Vision Systems (ICVS 06), New York, January 5-7, 2006.) and later extended in (Scaramuzza, D., Martinelli, A. and Siegwart, R., (2006). "A Toolbox for Easy Calibrating Omnidirectional Cameras", Proceedings to IEEE International Conference on Intelligent Robots and Systems (IROS 2006), Beijing China, October 7-15, 2006. ). A detailed introduction to this model is in section 19 of this Tutorial. Furthermore, you can also see a demo of how the toolbox works here. The Toolbox permits the user to easily and quickly cal)

statcom using hysteresis current control technique

找了好久，才找到这个mctoolbox,功能很强大(i am looking for a long time mctoolbox)

先得到一个定位初始估计值，再利用建立最大似然方程对这个定位初始估计值进行修正，从而得到更优定位结果值，方法更接近于最大似然方法。(Get the a position initial estimate, re-use to establish the maximum likelihood equations corrected for positioning the initial estimates, resulting in better positioning the resulting value is closer to the maximum likelihood method.)