CursDotNetSharp

Summary: Newton-Raphson method for all real roots of the polynomial. MATLAB Release: R11 Description: This M-file calculates all the real roots of the given polynomial. It calls syn_division, a synthetic division function, and derivate, differentiation function. (Summary: Newton-Raphson method for all real roots of the polynomial. MATLAB Release: R11 Description: This M-file calculates all the real roots of the given polynomial. It calls syn_division, a synthetic division function, and derivate, differentiation function.)

简单直线阵列遗传算法优化，可以实现对简单四元直线阵列的优化。(Simple genetic algorithm to optimize linear array, which can realize the optimization of simple quarternary linear array.)

用四阶亚当斯显式公式求解常微分方程初值问题是一种比较有效的方法(Adams with the fourth-order explicit formula for solving ODEs is a more effective method)

说明：  本程序由MATLAB编制成的用于计算观测数据的频率和周期。(This program is used to compute the frequence and periodical.)

说明：  matlab入手教程

说明：  CHAPTER 5 (C5 Folder) BASICS OF ELECTRIC MACHINES AND TRANSFORMATION Project 1: QD0 Transformation of Network Components SIMULINK file none MATLAB M-file none Project 2: Space Vectors SIMULINK file s2.mdl MATLAB M-file m2.m (also used by masked block) Project 3: Sinusoidal and Complex Quantities in QD0 SIMULINK file s3.mdl MATLAB M-file m3.m (also used by masked block)

Design a fuzzy system to approximate a function the function may not be defined analytically but the values of the function in n point is defined for example : x E [-3 3] g(x)=sin(x) the approximation is calculated a fuzzy set design our fuzzy function approximates sin function with an error less than 0.2 note : this program uses a function named isinrange so copy it to your directory

很多mtalab关于数据分析的源代码，欢迎各位童鞋下载(Many mtalab data analysis on the source code, to welcome you to download children s shoes)

用Matlab编程，实现解决该问题的单样本训练BP网络，设置一个停止迭代的误差Emin和最大迭代次数。在调试过程中，通过不断调整隐层节点数，学习率η，找到收敛速度快且误差小的一组参数。产生均匀分布在区间[-4，4]的测试样本，输入建立的模型得到输出，与Hermit多项式的期望输出进行比较计算总误差（运行5次，取平均值）(Using Matlab programming, to solve the problem of single sample training BP network, set a stop error iterations Emin and the maximum number of iterations. In the debugging process, by continuously adjusting the hidden layer nodes, learning rate η, fast convergence and find a set of parameters small errors. Produce a uniform distribution in the interval [4,4] of the test sample, the model has been established input output with the expected output Hermit polynomial calculated by comparing the total error (run 5 times the average))

这是一个牛顿插值的例子。输入差值点，计算4次牛顿插值函数值。(This is an example of Newton interpolation. Enter the difference points to calculate the value of 4 Newton interpolation function.)