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Raspberry Pi 的代码
kalman.m
function [sys,x0,str,ts]=kalman(t,x,u,flag,k)
switch flag,
case 0 %初始化设置
[sys,x0,str,ts]=mdlInitializeSizes;
case 3
sys=mdlOutputs(t,x,u,k);
case {1,2,4,9}
sys=[];
otherwise
error(['Unhandle
hrollfcoef.m
% Program 3-3
% hrollfcoef.m
%
% Generate coefficients of Nyquist filter
%
% programmed by H.Harada
%
function [xh] = hrollfcoef(irfn,ipoint,sr,alfs,ncc)
%****************** variables ****
hrollfcoef.m
% Program 3-3
% hrollfcoef.m
%
% Generate coefficients of Nyquist filter
%
% programmed by H.Harada
%
function [xh] = hrollfcoef(irfn,ipoint,sr,alfs,ncc)
%****************** variables ****
5-12.m
%例程5－12 利用特征向量法估计功率谱
% e.g.5-12.m for example5-12;
% to test function peig;
clf;
clear all;
% Generate the signal plus white noise and show
N=1024; % number of sampling dat
3-4.m
%例程3-4 产生锯齿波形
Fs=1000;
t=0:1/Fs:3;
x=sawtooth(2*pi*t);
y=sawtooth(2*pi*t,0.5);
z=sawtooth(2*pi*t,1);
subplot(3,1,1);
plot(t,x);
subplot(3,1,2);
plot(t,y);
subplot(3,1,3);
plo
3-12.m
%例程3-12 求解单位冲击响应的幅频
N=20;
a=[0.4 0.3 -1];
b=[1 -0.2 0.6 0.3];
x=[1 zeros(1,N-1)];
k=0:N-1;
y=filter(a,b,x);
Fs=1000;
w=0:pi/Fs:pi;
h=freqz(a,b,w);
subplot(2,1,1);
stem(k,y);
3-1.m
%例程3-1 计算序列抽样和与序列能量
t=(0:0.1:10)';
x=sin(2*pi*t)+2*cos(pi*t);
y=x+randn(size(t));
s=sum(x(1:100));
E=sum(abs(y).^2);
subplot(2,2,1);
plot(t,x);
title('X');
subplot(2,2,2);
plot(t,y);
ti
4-25.m
%例程4－25 基于频率抽样方法2实现Ⅲ型FIR数字带通滤波器
clear all;
N=41;
T1=0.1095;
alpha= (N-1)/2;
l=0:N-1;
wl= (2*pi/N)*l;
Hrs=[zeros(1,6),T1,ones(1,7),T1,zeros(1,11),T1,ones(1,7),T1,zeros(1,6)];
4-24.m
%例程4－24 基于频率抽样方法1实现Ⅰ型FIR数字高通滤波器
clear all;
N=61;
T1=0.1095;
T2=0.598;
alpha= (N-1)/2;
l=0:N-1;
wl= (2*pi/N)*l;
Hrs=[zeros(1,22),T1,T2,ones(1,14),T2,T1,zeros(1,21)]; %理想振幅采样响应
Hdr
4-1.m
%例程4－1 利用冲激响应不变法设计数字低通滤波器
%利用模拟巴特沃斯滤波器设计数字低通滤波器
%冲激响应不变法
wp=0.2*pi;
ws=0.3*pi;
Rp=1;
As=15;
T=1;
%性能指标
Rip=10^(-Rp/20);
Atn=10^(-As/20);
OmgP=wp*T;
OmgS=ws*T;
[N,OmgC]=buttord(OmgP,Omg