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/479405/6694518
m genrn.m
% genrn.m
% Scope: This MATLAB macro generates random numbers with normal
% (Gaussian) distribution, with mean and standard deviation
% specified
www.eeworm.com/read/264746/11303005
m moptimum.m
function moptimum
%Program moptimum is for designing I-stage optimum decimator
%or interpolator (I=1,2,3 or 4). The program computes the decimation
%factors, filter characteristics, and decim
www.eeworm.com/read/263959/11335743
m stats_1.m
% Script file: stats_1.m
%
% Purpose:
% To calculate mean and the standard deviation of
% an input data set containing an arbitrary number
% of input values.
%
% Record of revisi
www.eeworm.com/read/263959/11335749
m stats_2.m
% Script file: stats_2.m
%
% Purpose:
% To calculate mean and the standard deviation of
% an input data set containing an arbitrary number
% of input values.
%
% Record of revisi
www.eeworm.com/read/263959/11335761
m stats_3.m
% Script file: stats_3.m
%
% Purpose:
% To calculate mean and the standard deviation of
% an input data set, where each input value can be
% positive, negative, or zero.
%
% Reco
www.eeworm.com/read/263879/11338028
m std.m
function y = std(x,flag,dim)
%列状数据标准差
%例如
% A=[11 4 0.2;22 3 0.5;0 3 0.4];
% std(A)
%
%STD Standard deviation.
% For vectors, STD(X) returns the standard deviation. For matrices,
%
www.eeworm.com/read/400577/11572638
m gendatl.m
%GENDATL Generation of Lithuanian classes
%
% A = GENDATL(N,S)
%
% INPUT
% N Number of objects per class (optional; default: [50 50])
% S Standard deviation for the data generation (optional; d
www.eeworm.com/read/400577/11573363
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
www.eeworm.com/read/158463/11612709
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
%
www.eeworm.com/read/158463/11612749
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
%