代码搜索：significant
找到约 1,018 项符合「significant」的源代码
代码结果 1,018
www.eeworm.com/read/378510/9227864
thanks
Development contributors are listed in the AUTHORS file. Other community
members who have made significant contributions in other areas are listed
in this file:
Alan Stern
Ludovic Rousseau
Tim Robert
www.eeworm.com/read/275852/10790435
in index.html.in
define(`tref', ` $2
$3 ')
define(`lref', `$2');
www.eeworm.com/read/296774/7113513
def stab.def
/* Table of DBX symbol codes for the GNU system.
Copyright (C) 1988 Free Software Foundation, Inc.
This program is free software; you can redistribute it and/or modify
it under the terms of
www.eeworm.com/read/299984/7140541
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/460435/7251017
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/448427/7533622
h int128.h
/****************************************************************\
Copyright 2004 Enzo Michelangeli
This file is part of the KadC library.
KadC is free software; you can redistribute it and/or modi
www.eeworm.com/read/448427/7533641
h int128.h
/****************************************************************\
Copyright 2004 Enzo Michelangeli
This file is part of the KadC library.
KadC is free software; you can redistribute it and/or modi
www.eeworm.com/read/441245/7673235
m klldc.m
%KLLDC Linear classifier built on the KL expansion of the common covariance matrix
%
% W = KLLDC(A,N)
% W = KLLDC(A,ALF)
%
% INPUT
% A Dataset
% N Number of significant eigenvectors
% AL
www.eeworm.com/read/297233/8037873
def stab.def
/* Table of DBX symbol codes for the GNU system.
Copyright (C) 1988 Free Software Foundation, Inc.
This program is free software; you can redistribute it and/or modify
it under the terms of
www.eeworm.com/read/138860/13207127
m pdfb_tr.m
function ytr = pdfb_tr(y, s, d, ncoef)
% PDFB_TR Retain the most significant coefficients at certain subbands
%
% ytr = pdfb_tr(y, s, d, [ncoef])
%
% Input:
% y: output from PDFB
% s