代码搜索：Variance

找到约 2,271 项符合「Variance」的源代码

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m noisecu.m

function noise=noisecu(N); %NOISECU Analytic complex uniform white noise. % NOISE=NOISECU(N) computes an analytic complex white uniform % noise of length N with mean 0.0 and variance 1.0. % % Exampl
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m noisecu.m

function noise=noisecu(N); %NOISECU Analytic complex uniform white noise. % NOISE=NOISECU(N) computes an analytic complex white uniform % noise of length N with mean 0.0 and variance 1.0. % % Exampl
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m noisecu.m

function noise=noisecu(N); %NOISECU Analytic complex uniform white noise. % NOISE=NOISECU(N) computes an analytic complex white uniform % noise of length N with mean 0.0 and variance 1.0. % % Exampl
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m noisecu.m

function noise=noisecu(N); %NOISECU Analytic complex uniform white noise. % NOISE=NOISECU(N) computes an analytic complex white uniform % noise of length N with mean 0.0 and variance 1.0. % % Exampl
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www.eeworm.com/read/180302/9313192

m datanormalize.m

function [dc,md,mi]=datanormalize(da,choise,oldscale,oldmi) % each column as an variable is normalized by its standard variance % All rights Reserved, March 2006. Kaijun WANG [nr,nc] = size(da);
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m randrice.m

function a=randrice(Ak,sigma,N) % function a=randrice(Ak,sigma,N) % % This function creates a Ricean distributed random variable with mean % value Ak and variance sigma. A set of Nx1 values is co
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m noisecu.m

function noise=noisecu(N); %NOISECU Analytic complex uniform white noise. % NOISE=NOISECU(N) computes an analytic complex white uniform % noise of length N with mean 0.0 and variance 1.0. % % Exampl
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www.eeworm.com/read/362500/9995877

m anova1w.m

function anova1w(dat,alpha) %ANOVA1W One way analysis of variance % Calculates one way ANOVA table and tests significance of % between factors variation (it is assumed that each column % of the
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www.eeworm.com/read/362500/9995956

m anova2w.m

function anova2w(dat,alpha) %ANOVA2W Two way analysis of variance % Calculates two way ANOVA table and tests significance of % between factors variation (it is assumed that each column % of the
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www.eeworm.com/read/362152/10015669

m randn.m

function R=randn(M,N) % RANDN Normally distributed random numbers and matrices from % a normal distribution with mean 0.0 and variance 1.0. % usage: % R = randn(M,N) % % R: matrix of random values
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