代码搜索：preprocessing
找到约 856 项符合「preprocessing」的源代码
代码结果 856
www.eeworm.com/read/301959/13845511
m simpcomp2d.m
function [rmsecomp,fhat]=simpcomp2D(fname,f,dflt,rflt,prepr,nlarge)
%[rmsecomp,fhat]=simpcomp2D(fname,f,dflt,rflt,prepr,nlarge)
%
% This function compresses 2-dimensional signal by retaining given
www.eeworm.com/read/263454/11362178
c scaleprefix.c
{
// -------------------------------------------------------------------
// -------------------- scaling prefix -----------------------
// --------------------------------------------
www.eeworm.com/read/400577/11573051
m vertcat.m
%VERTCAT Vertical concatenation of datafiles (object extension)
%
% C = [A;B]
%
% The datafiles A and B are vertically concatenated, i.e. the
% objects of B are added to the dataset A. This is cons
www.eeworm.com/read/400577/11573136
m imread.m
%IMREAD Datafile overload
%
% IM = IMREAD(A,N)
%
% The images (raw data) of the datafile A are returned as a cell array.
% The preprocessing and postprocessing defined for the datafile are
%
www.eeworm.com/read/228658/14371282
m simpcomp2d.m
function [rmsecomp,fhat]=simpcomp2D(fname,f,dflt,rflt,prepr,nlarge)
%[rmsecomp,fhat]=simpcomp2D(fname,f,dflt,rflt,prepr,nlarge)
%
% This function compresses 2-dimensional signal by retaining given
www.eeworm.com/read/125092/14513621
m simpcomp2d.m
function [rmsecomp,fhat]=simpcomp2D(fname,f,dflt,rflt,prepr,nlarge)
%[rmsecomp,fhat]=simpcomp2D(fname,f,dflt,rflt,prepr,nlarge)
%
% This function compresses 2-dimensional signal by retaining given
www.eeworm.com/read/386050/8769437
m pls_apply.m
%pls_apply Partial Least Squares (applying)
%
% Y = pls_apply(X,B)
% Y = pls_apply(X,B,Options)
%
% INPUT
% X [N -by- d_X] the input data matrix, N samples, d_X variables
% B [d_X
www.eeworm.com/read/299984/7140686
m pls_apply.m
%pls_apply Partial Least Squares (applying)
%
% Y = pls_apply(X,B)
% Y = pls_apply(X,B,Options)
%
% INPUT
% X [N -by- d_X] the input data matrix, N samples, d_X variables
% B [d_X
www.eeworm.com/read/460435/7251162
m pls_apply.m
%pls_apply Partial Least Squares (applying)
%
% Y = pls_apply(X,B)
% Y = pls_apply(X,B,Options)
%
% INPUT
% X [N -by- d_X] the input data matrix, N samples, d_X variables
% B [d_X
www.eeworm.com/read/441245/7673382
m pls_apply.m
%pls_apply Partial Least Squares (applying)
%
% Y = pls_apply(X,B)
% Y = pls_apply(X,B,Options)
%
% INPUT
% X [N -by- d_X] the input data matrix, N samples, d_X variables
% B [d_X