sciaga_z_matlaba

实现turbo码的编码和解码，是一个递归卷积码的编解码的程序(Turbo code to achieve the encoding and decoding)

matlab编写的m序列产生器以及通过simulink7.01仿真实现的两个模型，最后给出了相关系数的计算代码(m prepared matlab serial generator as well as through two simulink7.01 simulation model, the correlation coefficient is given for calculating the code)

以中等纯度的精馏塔为研究对象，考虑到不等分子溢流的影响和非理想的汽液平衡，可以得到塔顶产品轻组分含量Y与回流量L之间的传递函数为： 其中由于现场环境干扰，输出带有测量噪声是（0，1）的正态分布序列，它的方差为ɑ=0.5。由于输出中带有很大的噪声信号，故将数字滤波技术中常见的低通滤波器由于偏差控制，滤掉其中的噪声信号，然后在对其进行PID计算，得到实际的控制量。在该方法在噪声较强的环境下，可以得到较好的控制效果。 控制要求： 1、 采用带低通滤波器的增量式PID将塔顶轻组分含量控制在0.99 2、 用ISTE法整定PID参数 3、 在控制过程中，到150周期加入幅度为-20 的阶跃干扰，在第300周期干扰消失。分析PID参数的抗干扰性。 (Medium-purity distillation column, taking into account ranging from molecular overflow and non-ideal vapor-liquid equilibrium, the transfer function between the light component content of the top product Y and the back flow L can be obtained as: Because the field of environmental interference, output with the measurement noise is a normal distribution (0,1) sequence, its variance ɑ = 0.5. As with a lot of noise in the output signal, it will be common in low-pass filter in the digital filtering techniques due to the bias control, filter out the noise signal, then its PID, the actual amount of control. In the strong noise environment, you can get better control effect. Control requirements: 1, using the incremental PID with a low-pass filter to the top of the tower content of light components in the 0.99 2, the method of ISTE tuning PID parameters 3, in the control process, to 150 cycles join the range of-20 step disturbance, disappearance of interference in the first 300 c)

无约束条件的粒子群优化算法代码，简单实用！(No constraints PSO algorithm code, simple and practical!)

完整的空间卫星轨道仿真程序以及空间卫星导航仿真程序。(Complete space orbit satellite navigation and space simulation program and simulation program.)

DH Animation of Robot

Fundamentals of Global Positioning System Receivers A Software Approach--中文译本名为《GPS软件接收机基础》，这是英文版。(Fundamentals of Global Positioning System Receivers A Software Approach)

FSK frequency shif keying simulation with matlab and Quadrature amplitude modulation QAM 16

tool box for grey wolf optimizer tool box for grey wolf optimizer

支持向量机方法，用matlab实现，用于分类检测、模式识别，人脸检测等(matlab implementation for classification detection, pattern recognition, face detection, etc.)