代码搜索：initial
找到约 10,000 项符合「initial」的源代码
代码结果 10,000
www.eeworm.com/read/337552/12358770
s pt2262.s
.module PT2262.C
.area text(rom, con, rel)
.dbfile C:\DOCUME~1\Administrator\桌面\PT2262_atmega8\PT2262.C
.dbfunc e initial_PORT _initial_PORT fV
.even
_initial_PORT::
.dbline -1
.dbline 2
www.eeworm.com/read/337552/12358791
o pt2262.o
XL
H 1 areas 6 global symbols
M PT2262.C
S push_gset1 Ref0000
S pop_gset1 Ref0000
A text size 56 flags 0
dbfile C:\DOCUME~1\Administrator\桌面\PT2262_atmega8\PT2262.C
dbfunc e initial_PORT 0 fV
www.eeworm.com/read/250952/12374174
h ad9851.h
#ifndef _AD9851_H_
#define _AD9851_H_
/*==============================================================*/
/*类型定义 */
/*=================
www.eeworm.com/read/336901/12407946
v me_tf.v
`timescale 1 ns / 1 ns
module me_tf ;
reg [7:0] din ;
reg rst ;
reg clk ;
reg wr ;
wire mdo ;
wire ready ;
me u1 (rst,clk,wr,din,ready,mdo) ;
initial begin
rst = 1'b0 ;
clk = 1'b0 ;
din = 8'h0 ;
wr
www.eeworm.com/read/234452/14112496
m goldseq_gen1.m
function goldseq = goldseq_gen1(offset)
% gold sequences generator
p = offset;
r=5;N=2^r-1;
s1(1:5)=[1 0 0 0 0 ]; %initial value 1
s2(1:5)=[1 0 0 0 0 ]; %initial value 1
f1=[1 0 0 1 0 1]; %特征多项
www.eeworm.com/read/234452/14112500
asv goldseq_gen1.asv
function goldseq = goldseq_gen(offset)
% gold sequences generator
p = offset;
r=5;N=2^r-1;
s1(1:5)=[1 0 0 0 0 ]; %initial value 1
s2(1:5)=[1 0 0 0 0 ]; %initial value 1
f1=[1 0 0 0 0 1 1]; %特征多
www.eeworm.com/read/234452/14112508
m goldseq_gen.m
function goldseq = goldseq_gen(offset)
% gold sequences generator
p = offset;
r=6;N=2^r-1;
s1(1:6)=[1 0 0 0 0 0]; %initial value 1
s2(1:6)=[1 0 0 0 0 0]; %initial value 1
f1=[1 0 0 0 0 1 1]; %特
www.eeworm.com/read/233999/14126335
a51 inclr.a51
;说明使用到的外部函数和外部变量
EXTRN CODE(CWE1, DWE1, CWE2, DWE2)
EXTRN DATA(COM, DAT)
;定义全局函数INITIAL(), CLEAR()
PUBLIC INITIAL, CLEAR
INITP SEGMENT CODE
INIROM SEGMENT CODE
RSEG INIROM
;定义内部变量：初始化变量数组T
www.eeworm.com/read/131588/14136275
m hmm_forward.m
function [Pout, Alpha] = HMM_Forward(a, b, initial_state, V)
% Find the probability of a finite state in a Markov chain using the HMM forward algorithm
%
% Inputs:
% a - Transition probabili