代码搜索：pattern
找到约 10,000 项符合「pattern」的源代码
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www.eeworm.com/read/470729/6907025
cpp render_style.cpp
/*
* This file is part of the DOM implementation for KDE.
*
* Copyright (C) 1999 Antti Koivisto (koivisto@kde.org)
* Copyright (C) 2004 Apple Computer, Inc.
*
* This library is free softwa
www.eeworm.com/read/191687/6958697
8 fill48.8
;
; create 48KB fill pattern
;
; (C)1998-2001 Pascal Dornier / PC Engines; All rights reserved.
; This file is licensed pursuant to the COMMON PUBLIC LICENSE 0.5.
db 0C000h DUP 0FFh
www.eeworm.com/read/467198/7020096
m kfm2.m
function kfm2(dataID)
% KFM2 Kohonen's feature map with 2-D output units.
% KFM2 is Kohonen's feature map with 2-D outputs.
% KFM2(1) --> data set in a square region.
% KFM2(2) --> data set in a t
www.eeworm.com/read/458682/7291440
sh realname.sh
#!/bin/bash
# realname.sh
#
# From username, gets "real name" from /etc/passwd.
ARGCOUNT=1 # Expect one arg.
E_WRONGARGS=65
file=/etc/passwd
pattern=$1
if [ $# -ne "$ARGCOUNT" ]
then
echo
www.eeworm.com/read/457876/7316238
vec fir.vec
% units default to ns %
START 0 ;
STOP 1495 ;
INTERVAL 5 ;
INPUTS clk ;
PATTERN
0 1 ; % relative vector values %
% CLOCK ticks every INTERVAL %
INPUTS rst;
PATTERN
www.eeworm.com/read/453925/7403733
c test.c
/* test.c: testing routines for regex.c. */
#include
#ifdef STDC_HEADERS
#include
#else
char *malloc ();
char *realloc ();
#endif
/* Just to be complete, we make both the sys
www.eeworm.com/read/453434/7420734
m fig3_57_59_61.m
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Figure 3.57
% Nested array
% Figure 3.59
% Desired beamformer
% Figure 3.61
% Beam patterns for broadband array:
% N=11, 500
www.eeworm.com/read/442927/7642019
m hclusteringdemo.m
function hClusteringDemo(pattern_mat, distance, level)
% LINKCLU Display the formation of hierarchical clustering step by step
%
% Usage: hClusteringDemo(pattern_mat, distance, level)
% pattern_ma
www.eeworm.com/read/442927/7642038
m linkclu.m
function hclustdm(pattern_mat, distance, level)
% LINKCLU Display the formation of hierarchical clustering step by step
%
% Usage: hclustdm(pattern_mat, distance, level)
% pattern_mat: pattern mat