代码搜索：Fitting

找到约 695 项符合「Fitting」的源代码

代码结果 695
热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/421190/10751496

score

------SCORE RESULT FOR FITTING------ RMSE= 35.9455 AR= 0.8337 NIP= 83 ------SCORE RESULT FOR FORECASTING------ MONTH 6 7 8 RMSE
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www.eeworm.com/read/273177/10924006

score

------SCORE RESULT FOR FITTING------ RMSE= 35.9455 AR= 0.8337 NIP= 83 ------SCORE RESULT FOR FORECASTING------ MONTH 6 7 8 RMSE
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www.eeworm.com/read/443857/7621770

score

------SCORE RESULT FOR FITTING------ RMSE= 35.9455 AR= 0.8337 NIP= 83 ------SCORE RESULT FOR FORECASTING------ MONTH 6 7 8 RMSE
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www.eeworm.com/read/434325/7874356

m a5algos.m

%--------------------------------------------------------------------------- %A5ALGOS % % NUMERICAL METHODS: MATLAB Programs, (c) John H. Mathews 1995 % To accompany the text: % NUMERICAL METHODS
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www.eeworm.com/read/254415/12139191

score

------SCORE RESULT FOR FITTING------ RMSE= 35.9455 AR= 0.8337 NIP= 83 ------SCORE RESULT FOR FORECASTING------ MONTH 6 7 8 RMSE
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www.eeworm.com/read/209404/15220602

m expfitxy.m

function estimates=expfitxy(x,y) %input x is 1-by-N vector % y is 1-by-N vector %output a is the coeficient of fitting formula y=a*exp(bx) model=@expxy; [estimates]=fminsearch(model,rand(1,2
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www.eeworm.com/read/209404/15220620

asv expfitxy.asv

function [estimates,model]=expfitxy(x,y) %input x is 1-by-N vector % y is 1-by-N vector model=@expxy; esttimates=fminsearch(model,rand(1,2)); %output a is the coeficient of fitting formula y
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www.eeworm.com/read/392270/8353537

vbw 数学.vbw

Maths = 92, 68, 455, 406, C, 68, 171, 436, 487, C Normal = 66, 66, 444, 413, C Sort = 43, 21, 421, 368, C Calculate = 47, 0, 425, 339, C Mathmatics = 110, 109, 487, 457, C SimpleBase = 67, 17, 43
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www.eeworm.com/read/132864/14069987

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Maths = 92, 68, 455, 406, C, 68, 171, 436, 487, C Normal = 66, 66, 444, 413, C Sort = 43, 21, 421, 368, C Calculate = 47, 0, 425, 339, C Mathmatics = 110, 109, 487, 457, C SimpleBase = 67, 17, 43
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www.eeworm.com/read/409759/11314475

m fitting complex analytic laws to data by means of genetic algorithms.m

function [coeff,RMSout]=FitLaw_GA(X,y,fh,Int,LB,UB) % % function [coeff,RMSout]=FitLaw_GA(X,y,fh,Int,LB,UB) % % The script fits a given general analytical law using Genetic Algorithms. % Such law
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