代码搜索：deviation
找到约 1,443 项符合「deviation」的源代码
代码结果 1,443
www.eeworm.com/read/300086/13936636
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));
www.eeworm.com/read/300086/13936704
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));
www.eeworm.com/read/134896/13971242
m igauss.m
%IGAUSS Gaussian smoothing kernel
%
% M = IGAUSS(W, SIGMA)
%
% Returns a W x W matrix with a unit amplitude Gaussian function of
% standard deviation SIGMA. The Gaussian is centered within the matrix
www.eeworm.com/read/235612/14061045
m dispavgstd.m
function dispavpstd(cvpavg, cvpstd)
f=gcf;
figure('menubar','none')
[nshots tmp] = size(cvpavg);
shots = 1:nshots;
% plot(cvpstd(:,1));
% hold on;
% plot(cvpavg(:,1));
errorbar(cvpavg(:,1), shots
www.eeworm.com/read/235612/14061127
m dispplust.m
function dispplust
% Display of the average Plus Time values with their
% corresponding standard deviation and fold for each receiver
f=gcf;
fbcoord=refdata('get','fbcoord');
plust=refdata('get','plus
www.eeworm.com/read/132953/14065248
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));
www.eeworm.com/read/132953/14065283
m normal.m
function y=normal(x,m,s)
% FUNCTION y=NORMAL(x,m,s)
% Gaussian distribution
% m=mean
% s=standard deviation
y=(1/sqrt(2*pi*s^2))*exp(-((x-m).^2)/(2*s^2));
www.eeworm.com/read/205038/15328008
html rms.html
Normalise / compute mean, standard deviation
Normalise time series and/or compute mean, standard deviation
rm
www.eeworm.com/read/203482/15357920
m igauss.m
%IGAUSS Gaussian smoothing kernel
%
% M = IGAUSS(W, SIGMA)
%
% Returns a W x W matrix with a unit amplitude Gaussian function of
% standard deviation SIGMA. The Gaussian is centered within the matrix
www.eeworm.com/read/202824/15372006
m igauss.m
%IGAUSS Gaussian smoothing kernel
%
% M = IGAUSS(W, SIGMA)
%
% Returns a W x W matrix with a unit amplitude Gaussian function of
% standard deviation SIGMA. The Gaussian is centered within the matrix