cm04

先生成这样的一幅500*500的RGB彩色图像：一个田字格，左上和右下是绿色，右上是红色，坐下是蓝色。并进行如下处理：（a）将该图像转换到HSI空间，用25*25的平均模板模糊H分量图像，再转换回RGB空间；（b）重复（a），只是这次处理的是S分量。最后简单分析结果。（内含实验报告） (Mr. into a 500* 500 RGB color image: a field word lattice, the upper left and lower right is green, the upper right is red the sit is blue. And be handled as follows: (a) the image into the HSI space, fuzzy H 25* 25 average template component image, and then converted back to RGB space (b) Repeat (a), only this time to deal with the S component . Finally, a simple analysis of the results. (Contains experimental report))

用于参数估计的极大似然估计法,简单，适用，方便(Maximum Likelihood method for parameter estimation，Simple, convenient, applicable)

Levinson-Durbin algorithm m file

关于matlab的几个实例和若干教程，国外写的(Several instances of matlab and tutorial written abroad)

产生雷达巴克码（Barker）信号，码内线性调频（LPM）。 RD_wave_mix.m 产生Baker码信号函数 test_wave_mix 测试函数(The Barker code (Baker code) radar signal, linear frequency modulation (LPM). RD_wave_mix.m Baker generated code signal function test_wave_mix test function)

永磁直驱风电机组机侧变流器控制simulink仿真(Permanent magnet direct drive wind turbine machine side converter control simulink simulation)

简单的模糊自适应鲁棒滑模控制程序，结合了模糊控制，鲁棒控制和滑模控制的优点(Simple fuzzy adaptive robust sliding mode control program, combined with fuzzy control, robust control and the advantages of sliding mode control)

EnMn 求一帧语音信号的短时能量和短时幅度函数(Seeking a short-time speech signal power and short range function)

this is code for Distance Regularized Level Set Evolution and Its Application to Image Segmentation paper. I used this code and it was correct and have true answers.

用matlab设计FIR维纳滤波器 假设一个点目标在x，y平面上绕单位圆做圆周运动，由于外界干扰，其运动轨迹发生了偏移。其中，x方向的干扰为均值为0，方差为0.05的高斯噪声；y方向干扰为均值为0，方差为0.06的高斯噪声。用该滤波器处理观测信号，得到其最佳估计。(FIR Wiener filter design using matlab Suppose a point target in the x, y plane around the unit circle in a circular motion due to external interference, its trajectory shift occurred. Which, x the direction of the interference of mean 0 and variance of 0.05 Gaussian noise y direction of the disturbance is zero mean Gaussian noise variance 0.06. Observed with the filter processing signal, to get the best estimate.)