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/311447/13630915
m pdfb_tr.m
function ytr = pdfb_tr(y, s, d, ncoef)
% PDFB_TR Retain the most significant coefficients at certain subbands留住最显着的系数，在某些子带
%
% ytr = pdfb_tr(y, s, d, [ncoef])
%
% Input:
% y: output from PDF
www.eeworm.com/read/144216/5752559
t inc.t
#!./perl
print "1..12\n";
# Verify that addition/subtraction properly upgrade to doubles.
# These tests are only significant on machines with 32 bit longs,
# and two's complement negation, but shoul
www.eeworm.com/read/136072/5874433
def stab.def
/* Table of DBX symbol codes for the GNU system.
Copyright (C) 1988, 1997 Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can r
www.eeworm.com/read/131315/5930800
s muld.s
/*
* Copyright (c) 1986, 1993
* The Regents of the University of California. All rights reserved.
*
* This code is derived from software contributed to Berkeley by
* Computer Consoles Inc.
*
*
www.eeworm.com/read/131315/5936169
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/119864/6080920
def stab.def
/* Table of DBX symbol codes for the GNU system.
Copyright (C) 1988, 1997 Free Software Foundation, Inc.
This file is part of the GNU C Library.
The GNU C Library is free software; you can r
www.eeworm.com/read/101082/6243091
1c l6.1c
#print
One thing to keep in mind is that outside of
$ signs, spaces are significant just as they
were before. Inside $ signs, spaces are significant
only as delimiters, and will not add any space
to
www.eeworm.com/read/407068/11430440
h kxp74.h
/*****************************************************************************
* kxp74.h
* Lab 6: Final Project
* ECE 476: Digital Systems Design Using Microcontrollers
* Cornell University
www.eeworm.com/read/400577/11573199
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