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/457219/7332196
m da_lsqs.m
%
% da_lsqs
%
% Least squares regression entry point
%
%
% Clear the screen
%
da_front;
drawnow;
%
% Make sure that none of the variables have a zero
% standard deviation
%
s=std(dat
www.eeworm.com/read/452217/7445380
m da_lsqs.m
%
% da_lsqs
%
% Least squares regression entry point
%
%
% Clear the screen
%
da_front;
drawnow;
%
% Make sure that none of the variables have a zero
% standard deviation
%
s=std(dat
www.eeworm.com/read/206731/7457177
m da_lsqs.m
%
% da_lsqs
%
% Least squares regression entry point
%
%
% Clear the screen
%
da_front;
drawnow;
%
% Make sure that none of the variables have a zero
% standard deviation
%
s=std(dat
www.eeworm.com/read/441245/7672685
m rnnc.m
%RNNC Random Neural Net classifier
%
% W = RNNC(A,N,S)
%
% INPUT
% A Input dataset
% N Number of neurons in the hidden layer
% S Standard deviation of weights in an input layer (default: 1
www.eeworm.com/read/298649/7947895
m da_lsqs.m
%
% da_lsqs
%
% Least squares regression entry point
%
%
% Clear the screen
%
da_front;
drawnow;
%
% Make sure that none of the variables have a zero
% standard deviation
%
s=std(dat
www.eeworm.com/read/145776/12703176
m lms5.m
%LMS5 Problem 2.1
%
% 'ifile.mat' - input file containing:
% K - iterations
% H - FIR channel
% Neq - equalizer order
% sigman - standard deviation of noise at channel ou
www.eeworm.com/read/244076/12892408
m da_lsqs.m
%
% da_lsqs
%
% Least squares regression entry point
%
%
% Clear the screen
%
da_front;
drawnow;
%
% Make sure that none of the variables have a zero
% standard deviation
%
s=std(dat
www.eeworm.com/read/137229/13339015
m da_lsqs.m
%
% da_lsqs
%
% Least squares regression entry point
%
%
% Clear the screen
%
da_front;
drawnow;
%
% Make sure that none of the variables have a zero
% standard deviation
%
s=std(dat
www.eeworm.com/read/302326/13837673
m lms5.m
%LMS5 Problem 2.1
%
% 'ifile.mat' - input file containing:
% K - iterations
% H - FIR channel
% Neq - equalizer order
% sigman - standard deviation of noise at channel ou
www.eeworm.com/read/309192/6342043
m lms5.m
%LMS5 Problem 2.1
%
% 'ifile.mat' - input file containing:
% K - iterations
% H - FIR channel
% Neq - equalizer order
% sigman - standard deviation of noise at channel ou