代码搜索:Fitting

找到约 695 项符合「Fitting」的源代码

代码结果 695
www.eeworm.com/read/409142/11345205

m curvefit.m

Function CurveFit(aData, sTarget1, sTarget2, sTarget3) 'MATLAB regression and curve fitting macro MLPutMatrix "data", aData MLEvalString "y = data(:,3)" MLEvalString "n = len
www.eeworm.com/read/253950/12173640

m demmdn1.m

%DEMMDN1 Demonstrate fitting a multi-valued function using a Mixture Density Network. % % Description % The problem consists of one input variable X and one target variable % T with data generated by
www.eeworm.com/read/339665/12211680

m demmdn1.m

%DEMMDN1 Demonstrate fitting a multi-valued function using a Mixture Density Network. % % Description % The problem consists of one input variable X and one target variable % T with data generated by
www.eeworm.com/read/150905/12250521

m demmdn1.m

%DEMMDN1 Demonstrate fitting a multi-valued function using a Mixture Density Network. % % Description % The problem consists of one input variable X and one target variable % T with data generated by
www.eeworm.com/read/232704/14185046

m curvefit.m

Function CurveFit(aData, sTarget1, sTarget2, sTarget3) 'MATLAB regression and curve fitting macro MLPutMatrix "data", aData MLEvalString "y = data(:,3)" MLEvalString "n = len
www.eeworm.com/read/220289/14843844

m demmdn1.m

%DEMMDN1 Demonstrate fitting a multi-valued function using a Mixture Density Network. % % Description % The problem consists of one input variable X and one target variable % T with data generated by
www.eeworm.com/read/215382/15062889

m curvefit.m

Function CurveFit(aData, sTarget1, sTarget2, sTarget3) 'MATLAB regression and curve fitting macro MLPutMatrix "data", aData MLEvalString "y = data(:,3)" MLEvalString "n = len
www.eeworm.com/read/213342/15136860

m curvefit.m

Function CurveFit(aData, sTarget1, sTarget2, sTarget3) 'MATLAB regression and curve fitting macro MLPutMatrix "data", aData MLEvalString "y = data(:,3)" MLEvalString "n = len
www.eeworm.com/read/212307/15160152

m demmdn1.m

%DEMMDN1 Demonstrate fitting a multi-valued function using a Mixture Density Network. % % Description % The problem consists of one input variable X and one target variable % T with data generated by
www.eeworm.com/read/13871/284633

m demmdn1.m

%DEMMDN1 Demonstrate fitting a multi-valued function using a Mixture Density Network. % % Description % The problem consists of one input variable X and one target variable % T with data generated