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