f_Stationary

线性规划，优化设计作业优化设计作业。。。。。。。。。(linear。。。。)

传统的宽带信号中抑制正弦干扰的方法是采用陷波器(notch filter),为此需要精确知道干扰正弦的频率.然而当干扰正弦频率是缓慢变化时,且选频率特性要求十分尖锐时,则最好采用自适应噪声抵消的方法.下图是用一个二阶FIR的LMS自适应滤波器消除正弦干扰的一个方案。该代码实现了以下功能： 1) 借助MATLAB画出了滤波器的误差性能曲面和误差性能曲面的等值曲线； 2） 给出了最陡下降法以及LMS算法的计算公式； 3） 用MATLAB产生了方差为0.05, 均值为0白噪音S(n)，并画出某次采样得到的波形； 4） 根据 2）中的公式，并利用 3）中产生的S(n)，在 1）中的误差性能曲面的等值曲线上叠加画出了采用最陡下降法以及LMS法时H(n)的在叠代过程中的轨迹曲线； 5）用MATLAB计算并画出了LMS法时误差随时间n的变化曲线（对应S(n)的某一次的一次实现）和e(n)波形； 6）在 1）中的误差性能曲面的等值曲线上，叠加画出采用LMS法得到的100次实验中的H(n)的平均值的轨迹曲线； 7）最终对结果进行了分析，具体见压缩包的word文档。 (Wideband signal in the conventional sinusoidal interference suppression method is the use notch filter (notch filter), this requires precise knowledge of the frequency of a sinusoidal interference . However, when the interference frequency sinusoidal changes slowly , and the selected frequency characteristic requirements are very sharp , then best use of adaptive noise cancellation method . following figure is a second-order FIR LMS adaptive filter to eliminate a program sinusoidal interference . The code implements the following functions:   A ) draw with MATLAB error performance of the filter surface and the surface contour error performance curve 2 ) gives the steepest descent method and the LMS algorithm formula 3 ) generated using MATLAB variance of 0.05 with a mean of 0 white noise S (n), and draw a particular sampling waveform 4 ) based on 2 ) of the formula , and use 3 ) generated in S (n), in a ) the error performance curves superimposed on the surface contour pl)

this file give most famous and important simulation programming codes of chaotic signals map generation

说明：  matlab基本差分进化算法，仅供参考，包括种群变异，交叉、选择生成下一代种群的过程(matlab basic differential evolution algorithm, for reference, including the population variation, crossover, select the process to generate the next generation of population)

filter design sigma delta filter(filter design sigma delta filter)

Hidden-Unit Conditional Random Fields 工具箱，可以用于训练linearCRF和和L.J.P. van der Maaten, M. Welling 提出的huCRF(We provide Matlab code that implements the training and evaluation of hidden-unit CRFs, as well as code to reproduce the results of our experiments. The code implements four different training algorithms: (1) a batch learner that uses L-BFGS, (2) a stochastic gradient descent learner, (3) an online perceptron training algorithm, and (4) an online large-margin perceptron algorithm. The code can also be used to perform (conditional) herding in hidden-unit CRFs. )

曲面画法大全matlabSurface painting Daquan(Surface painting Daquan)

PLL desgin block for matlab

基于matlab的7-4线性分组器设计，简单易懂，有界面(7-4 matlab-based linear block design, easy to understand, interface)

利用matlab对图像进行灰度调整、拉伸处理和边缘检测(Use matlab image grayscale adjustment, stretch processing and edge detection)