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转载matlab的学习经验供新手参考，对你也许会有用！(Reprint matlab novice learning experience for reference, may be useful for you!)

利用matlab编写的根据连续分离变量方法设计的优化程序包(Using matlab to prepare the basis for a continuous optimization of separation of variables designed package)

说明：  神经网络与matlab7的实现 配套资料下载 .m格式(neural network and the realization matlab7 supporting information downloaded. M format)

Synthetic Aperture Radar Imaging Simulated in MATLAB

trust region method optiomizatiom method

说明：  SAR的MATLAB程序，这里主要是介绍传统的RD算法， 对初学者还是可以的(SAR in the MATLAB program, here is to introduce the traditional RD algorithm, for beginners or the possible)

用matlab仿真来实现lms算法和NLMS算法(lms algorithm)

一个很简单的用MATLAB编写的求信号分形盒维数的程序(A very simple request signal using MATLAB fractal dimension of the box)

E=input( enter the generator voltage: ) V=input( enter the infinite bus voltage: ) Gx=input( enter the reactance of generator: ) L1x=input( enter the line reactance: ) L2x=input( enter the line reactance: ) L3x=input( enter the line reactance: ) L4x=input( enter the line reactance: ) Pi=input( enter the input power: ) X1=Gx+L1x+((L2x*L3x)/(L2x+L3x))+L4x Pm1=E*V/X1 DO=asin(Pi/Pm1) A=((L2x*L3x)/(2*(L2x+L3x))) C=A B=((L3x/2)^2)/(L2x+L3x) X2=(Gx+L1x+A)+(L4x+A)+(Gx+L1x+A)*(A+L4x)/B Pm2=(E*V)/X2 X3=Gx+L1x+L2x+L4x Pm3=(E*V)/X3 DC=input( enter the fault clearing angle: ) Dm=(3.14-asin(Pi/Pm3)) a1=quad( sin ,DO,DC) A1=(Pi*(DC-DO)-Pm2*a1) a2=quad( sin ,DC,Dm) A2=Pm3*a2-Pi*(Dm-DC) if(A2>=A1) disp( the system is stable ) else disp( the system is unstable ) end Dcc=acos((Pi*(Dm-DO)-Pm2*(cos(DO))+Pm3*(cos(Dm)))/(Pm3-Pm2)) disp( critical clearing angle: ) Dcc

0_Linear：线性回归练习 1_LogistRegression：逻辑回归练习 2_boston：波士顿房价预测 3_regularization：正则化 5_stock：股票价格预测 6_CTR：点击率预测 7_all_model：回归与分类模型 8_muticlass：多分类练习 9_regression_implement：不同回归算法tf实现(0_Linear. 1_LogistRegression. 2_boston. 3_regularization. 5_stock. 6_CTR. 7_all_model. 8_muticlass. 9_regression_implement.)