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Branch line coupler design using Matlab

说明：  按FPE定阶的 源程序：fpe.cpp M序列：M序列.txt 白噪声：Gauss.txt 程序中先用依模型阶次递推算法估计模型的参数，再用fpe方法判断模型的阶次。 程序运行结果如下： n: 1 判断阶次FPE的值: 0.0096406 -0.481665 1.07868 n: 2 判断阶次FPE的值: 0.00875755 -0.446739 0.00498181 1.07791 0.0527289 n: 3 判断阶次FPE的值: 0.0087098 -0.459433 0.120972 -0.0569228 1.07814 0.0390757 0.116982 n: 4 判断阶次FPE的值: 0.000396884 -0.509677 0.4501 -0.200906 0.0656188 1.07991 -0.0156362 0.442989 0.0497236 n: 5 判断阶次FPE的值: 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771 n: 6 判断阶次FPE的值: 3.23349e-007 -1.14659 0.76933 -0.487651 0.329676 -0.10377 -0.00440907 1.07999 -0.703574 0.447253 -0.235282 0.113587 0.00479688 从以上结果可以看出，当n=5时，fpe值最小，所以这时的模型阶次和参数估计值为最优结果： 3.2095e-007 -1.18415 0.813123 -0.517862 0.34881 -0.116864 1.07999 -0.744141 0.474462 -0.253112 0.122771(err)

都是关于空间普估计算法，其中有解相干和非相干算法以及它们之间的对比( the spatial spectrum estimation)

algorithme genitique

大学数值分析算法，快速扩展随机生成树算法，结合PCA的尺度不变特征变换(SIFT)算法。( University of numerical analysis algorithms, Rapid expansion of random spanning tree algorithm, Combined with PCA scale invariant feature transform (SIFT) algorithm.)

说明：  协调控制算法，基于发电厂锅炉与汽轮机模型，首先将模型离散化，然后实施控制算法(Coordinated control algorithm, based on power plant boiler and steam turbine model, discrete model first and then the implementation of control algorithms)

deconvolution function to reconstruct impulse response

说明：  光伏并网系统中的孤岛效应仿真研究，一个非常好的参考论文资料。(Photovoltaic grid system island effect of simulation research, a very good reference data.)

some FEM applications with MATLAB

非线性曲线拟合是已知输入向量xdata和输出向量ydata，并且知道输入与输出的函数关系为ydata=F(x, xdata)，但不知道系数向量x。今进行曲线拟合，求x使得输出的如下最小二乘表达式成立： min Σ(F(x,xdatai)-ydatai)^2(Nonlinear curve fitting is a known input and output vectors xdata vector ydata, and know the relationship between the input and output functions for ydata = F (x, xdata), but do not know the coefficient vector x. As least-squares curve fitting expression today, find x such that the output of the establishment: min Σ (F (x, xdatai)-ydatai) ^ 2)