代码搜索:Generates

找到约 10,000 项符合「Generates」的源代码

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m isfixed.m

%ISFIXED Test on fixed mapping % % I = ISFIXED(W) % ISFIXED(W) % % True if the mapping type of W is 'fixed' (see HELP MAPPINGS). If called % without an output argument ISFIXED generates an erro
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m iscombiner.m

%ISCOMBINER Test whether the argument is a combiner mapping % % OK = ISCOMBINER(W) % ISCOMBINER(W) % % INPUT % W Mapping % % OUTPUT % OK 1/0 indicating if the mapping type of W is COMBINER
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m istrained.m

%ISTRAINED Test on trained mapping % % I = ISTRAINED(W) % ISTRAINED(W) % % True if the mapping type of W is 'trained' (see HELP MAPPINGS). If % called without an output argument ISTRAINED gener
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m isuntrained.m

%ISUNTRAINED Test on untrained mapping % % I = ISUNTRAINED(W) % ISUNTRAINED(W) % % True if the mapping type of W is 'untrained' (see HELP MAPPINGS). % If called without an output argument ISUNTR
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m gendatsin.m

%GENREGSIN Generate sinusoidal regression data % % X = GENDATSIN(N,SIGMA) % % INPUT % N Number of objects to generate % SIGMA Standard deviation of the noise % % OUTPUT % X Reg
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m gngauss.m

function [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(sgma) % [gsrv1,gsrv2]=gngauss % GNGAUSS generates two independent Gaussian random variables with mean %
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m gngauss.m

function [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(sgma) % [gsrv1,gsrv2]=gngauss % GNGAUSS generates two independent Gaussian random variables with mean %
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m gngauss.m

function [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(sgma) % [gsrv1,gsrv2]=gngauss % GNGAUSS generates two independent Gaussian random variables with mean %
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m gngauss.m

function [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(sgma) % [gsrv1,gsrv2]=gngauss % GNGAUSS generates two independent Gaussian random variables with mean %
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m gngauss.m

function [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(m,sgma) % [gsrv1,gsrv2]=gngauss(sgma) % [gsrv1,gsrv2]=gngauss % GNGAUSS generates two independent Gaussian random variables with mean %