fangxiangtu

能够实现定点小数的机器数表示、定点小数的变形补码加减运算、定点小数的原码一位乘法运算和浮点数的加减运算。(Able to achieve fixed-point decimal number of machines that the deformation of complement fixed-point decimal addition and subtraction operations, the original code a fixed-point decimal multiplication and floating-point operations of addition and subtraction.)

说明：  matlab的差分算法实现以及粒子群优化算法介绍 (matlab differential algorithms and particle swarm optimization algorithm introduced)

This is a matlab code denoise_main

边界元算法求解正方形导热问题实例。一个简单的二维导热模型，用BEM算法求解，用于学习边界元编程。(Boundary element method for solving square conduction problem instances. A simple two-dimensional heat conduction model, using BEM algorithm for learning boundary element programming.)

关于复杂网络的聚类系数算法，用matlab计算，矩阵为稀疏矩阵。(clustering_coefficients(A) returns the clustering coefficients for all vertices in A. The clustering coefficient is the ratio of the number of edges between a vertex s neighbors to the total possible number of edges between the vertex s neighbors. )

pfc boost converter single phase

mlem进行图像重建，可以试一下，还是可以跑的，和一本书上的代码是一致的。(MLEM algorithm which is a great tool to reconstruct the original 3D image and it will help you develop the skills of matlab coding.)

MATLAB SISO Design Tool.rar

针对insar影像的goldstein 相位滤波器(goldstein insar phase filter)

任务： 1） 借助MATLAB画出误差性能曲面和误差性能曲面的等值曲线（参考PPT2.1第17页的两幅图）； 2） 写出最陡下降法以及LMS算法的计算公式（取 ）； 3） 用MATLAB产生方差为0.05, 均值为0白噪音S(n)，并画出某次采样得到的波形（即产生任意一个噪声随机序列）； 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（参考PPT2.1第17页的右下图的曲线1和曲线2）。 5）用MATLAB计算并画出LMS法时 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； 注意：某一次实现的结果并不能从统计的角度反映实验的结果 的正确性，为得到具有统计特性的实验结果，可用足够多次的 实验结果的平均值作为实验的结果。用MATLAB计算并画出 采用LMS法时，J(n)的100次实验结果的平均值随时间n的变 化曲线（即 生成随机噪声信号并计算结果，重复执行100次， 求平均结果）。 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； (Task: 1 ) Draw with MATLAB error performance surface and surface contour error performance curve ( refer PPT2.1 two chart on page 17 ) 2 ) Write the steepest descent method and the LMS algorithm formula ( take ) 3 ) Using MATLAB to generate variance of 0.05 with a mean of 0 white noise S (n), and draw a particular sampling waveform ( ie, any noise generated random sequence ) 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 plot using the steepest descent method and the LMS method when H (n) the iterative process in the trajectory curve ( refer PPT2.1 page 17 bottom right of the curves 1 and 2 ) . 5 ) using MATLAB LMS method is used calculate and draw the curve with time n (corresponding to S (n) of a first implementation of a ) and e (n) waveform Note : in a first implementation of the results are not reflected from a statistical point of view of accuracy of the experimental results ,)