代码搜索：average
找到约 5,196 项符合「average」的源代码
代码结果 5,196
www.eeworm.com/read/481244/6645928
c restoration_sink.pr.c
/* Process model C form file: Restoration_sink.pr.c */
/* Portions of this file copyright 1992-2001 by OPNET Technologies, Inc. */
/* This variable carries the header into the object file */
www.eeworm.com/read/162313/10315759
m ekf_3dcv_filter.m
%参考文献
%Decoupling joint probabilistic data association algorithm for multiple target tracking
%杂波环境下多传感器的数据融合
%三维常速CV模型
clear all;
clc;
T=1;
www.eeworm.com/read/272822/10943007
m ekf.m
%参考文献
%Decoupling joint probabilistic data association algorithm for multiple target tracking
%杂波环境下多传感器的数据融合
%三维常速CV模型
clear all;
clc;
T=1;
www.eeworm.com/read/150263/12301545
m ekf_3dcv_filter.m
%参考文献
%Decoupling joint probabilistic data association algorithm for multiple target tracking
%杂波环境下多传感器的数据融合
%三维常速CV模型
clear all;
clc;
T=1;
www.eeworm.com/read/338384/12310580
m ekf_3dcv_filter.m
%参考文献
%Decoupling joint probabilistic data association algorithm for multiple target tracking
%杂波环境下多传感器的数据融合
%三维常速CV模型
clear all;
clc;
T=1;
www.eeworm.com/read/295526/8156076
m zbhj.m
%参考文献
%Decoupling joint probabilistic data association algorithm for multiple target tracking
%杂波环境下多传感器的数据融合
%三维常速CV模型
clear all;
clc;
T=1; % 采样周期
hits=2000; % 采样点数
MCNum=10; % Monte Ca
www.eeworm.com/read/412485/11197876
m ekf_3dcv_filter.m
%参考文献
%Decoupling joint probabilistic data association algorithm for multiple target tracking
%杂波环境下多传感器的数据融合
%三维常速CV模型
clear all;
clc;
T=1;
www.eeworm.com/read/431865/8648808
m huisegm.m
function GM=huise(data,N)
data=[3.936;4.575;4.968;5.063;5.968;5.507];
T=length(data);
N=5;
X0=data;
for i=2:T
X1(1)=X0(1);
X1(i)=X1(i-1)+X0(i); %用AGO生成一阶累加生成模块
end
for i=1
www.eeworm.com/read/197702/7973873
c smoke detector.c
//******************************************************************************
// Smoke Detector Code for F2002
//
// THIS PROGRAM IS PROVIDED "AS IS". TI MAKES NO WARRANTIES OR
// REPRESENTATI
www.eeworm.com/read/238753/13326819
m huisegm.m
function GM=huise(data,N)
T=length(data);
X0=data;
for i=2:T
X1(1)=X0(1);
X1(i)=X1(i-1)+X0(i); %用AGO生成一阶累加生成模块
end
for i=1:T-1
M(i)=-(0.5*(X1(i)+X1(i+1)));
end
B=zeros