代码搜索：plot
找到约 10,000 项符合「plot」的源代码
代码结果 10,000
www.eeworm.com/read/489747/6469239
svn-base exp2.m.svn-base
X=-2:0.01:4;
Y=normpdf(X,1,1/2);
subplot(1,2,1);
axis on;
plot(X,Y);
axis square;
title('pdf of normal');
Y=normcdf(X,1,1/2);
subplot(1,2,2);
plot(X,Y);
title('cdf of normal');
axis square;
www.eeworm.com/read/489747/6469247
m exp2.m
X=-2:0.01:4;
Y=normpdf(X,1,1/2);
subplot(1,2,1);
axis on;
plot(X,Y);
axis square;
title('pdf of normal');
Y=normcdf(X,1,1/2);
subplot(1,2,2);
plot(X,Y);
title('cdf of normal');
axis square;
www.eeworm.com/read/489361/6470532
m psk_8.m
%============= 2008.4.21 ======%
%========== “根” 升余弦 脉冲
clear;
clc;
fs=12000; % sample rate
ts=1/fs;
tb=ts*5;
fc=1800; % carrier frequency
df=1;
a
www.eeworm.com/read/489510/6471968
txt classification2.txt
%prony法模态参数识别
%%%%%%%%%%%%%%%%%%%%%
%clear
clc
close all hidden
format long
%%%%%%%%%%%%%%%%%%%%%%%%%%%
fni=input('prony模式识别数据文件名:','s');
%fni=out2.signals.values, 'DisplayName', 'out2.signals
www.eeworm.com/read/489524/6472515
m fig9_20.m
clear all
eps = 0.0000001;
npts = 5000;
del = 1./ 5000.;
t = 0. : del : 1.;
% generate input sequence
inp = 1.+ t.^3 + .5 .*t.^2 + cos(2.*pi*5 .* t) ;
% read the intial estimate for the state v
www.eeworm.com/read/489524/6472516
m fig9_21.m
clear all
eps = 0.0000001;
npts = 5000;
del = 1./ 5000.;
t = 0. : del : 1.;
% generate input sequence
inp = 1.+ t.^3 + .5 .*t.^2 + cos(2.*pi*5 .* t) ;
% read the intial estimate for the state v
www.eeworm.com/read/489524/6472518
m fig9_28.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2) + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurement vector H=[1,0,0]
% this is the
www.eeworm.com/read/489524/6472519
m fig9_27.m
clear all
npts = 2000;
del = 1/2000;
t = 0:del:1;
inp = (1+.2 .* t + .1 .*t.^2);% + cos(2. * pi * 2.5 .* t);
X0 = [1,.1,.01]';
% it is assumed that the measurmeny vector H=[1,0,0]
% this is the
www.eeworm.com/read/489131/6474229
m wiener1.m
%实例一程序_维纳滤波的计算机实现
%Script by loyal
%改程序是学习维纳滤波时所使用的程序，通过对此程序的学习，可以加深我们对维纳滤波基本原理的理解
%初步处理，并接受输入数据，包括信号样本个数L和滤波器阶数N
%Script by loyal
clear all
close all
L=input('L=');
N=input('N=');
a=0.95;
%
www.eeworm.com/read/489315/6478521
m runclarkemodel.m
%
% Multipath enviroment for Narrowband channel using Clarke's model
%
% Initialize ============================================================
clear
close all
clc
% basic inputs ===========