MIT-MRAC-normalization

说明：  本程序产生一个智能天线系统的信道模型，每一条多径都服从瑞利衰落。(This procedure generates a smart antenna system channel model, are subject to each multipath Rayleigh fading.)

Generates a codgray code. It is used when we don t have the communications package in our matlab

这个Matlab图形用户界面允许用户计算圆形，椭圆形和任意形状的广义极化张量。此计算的近似算法，该算法是基于Capdeboscq等人开发出一种方法。 (This Matlab GUI allows the user to compute the GPT of disks, ellipses, and arbitrary imported shapes. The approximating algorithm that does this computation is based off a method developed by Capdeboscq et al. )

实现两个信号的循环卷积，同时在满足一定条件时可以用来计算线性卷积。(Realization of convolution of two signals, at the same time can under certain conditions to calculate linear convolution.)

control system simulink 3

线性滤波中的最陡下降法和LMS自适应算法的代码实现，两种算法进行比较，并画出了迭代轨迹曲线(Achieve linear filter method of steepest descent and the code of the LMS adaptive algorithm, two algorithms are compared, and draw the curve of the iterative trajectory)

MATLAB实现语音去噪处理，测试已经通过了(Speech Denoising MATLAB realize treatment, testing has been adopted)

An object oriented Circular buffer implementation. Matlab version 7+ is required,

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)

Self organized map implementation in matlab