代码搜索：Variance

找到约 2,271 项符合「Variance」的源代码

代码结果 2,271
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m ds.m

function z=ds(nt) % z=ds(nt): % Function to analyze the degree of stationarity of data nt(n,m) by % calculating the variance for each n, where n specifies the number % of frequency
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www.eeworm.com/read/398034/8009063

m sa_ex7_14.m

% root-Min-Norm AOA estimation for a M = 4 element array with noise variance = .1 % use time averages instead of expected values by assuming ergodicity of the mean and % ergodicity of the correlati
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www.eeworm.com/read/398034/8009129

m sa_ex7_13.m

% root-MUSIC AOA estimation for a M = 6 element array with noise variance = .1 % use time averages instead of expected values by assuming ergodicity of the mean and % ergodicity of the correlation.
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www.eeworm.com/read/397477/8043482

m modskew.m

function [chm, snrk] = modskew(ch,sk,p); % Adjust the sample skewness of a vector/matrix, using gradient projection, % without affecting its sample mean and variance. % % This operation is not an ort
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www.eeworm.com/read/142092/12963102

m ds.m

function z=ds(nt) % z=ds(nt): % Function to analyze the degree of stationarity of data nt(n,m) by % calculating the variance for each n, where n specifies the number % of frequency
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www.eeworm.com/read/319478/13450855

rb rceg.rb

MRPP R BY C CONTINGENCY TABLE ANALYSIS (EXCESS) .62873634 = OBSERVED VALUE OF DELTA-B .56692803 = EXPECTED VALUE OF DELTA-B .38107617E-03 = VARIANCE OF
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www.eeworm.com/read/319478/13450892

ra rceg.ra

MRPP R BY C CONTINGENCY TABLE ANALYSIS (EXCESS) .62873634 = OBSERVED VALUE OF DELTA-B .66774194 = EXPECTED VALUE OF DELTA-B .56745267E-04 = VARIANCE OF
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www.eeworm.com/read/317326/13505925

m sa_ex7_14.m

% root-Min-Norm AOA estimation for a M = 4 element array with noise variance = .1 % use time averages instead of expected values by assuming ergodicity of the mean and % ergodicity of the correlati
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www.eeworm.com/read/317326/13505960

m sa_ex7_13.m

% root-MUSIC AOA estimation for a M = 6 element array with noise variance = .1 % use time averages instead of expected values by assuming ergodicity of the mean and % ergodicity of the correlation.
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www.eeworm.com/read/310212/13655106

m vmquantc.m

function [im, map] = vmquantc( r, g, b, k, Q, dith, Qe ) %VMQUANTC Variance Minimization Color Quantization (MEX file). % VMQUANTC implements the color quantization algorithm for % the function
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