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chap7_9.m

%Discrete Kalman filter for PID control %Reference kalman_2rank.m %x=Ax+B(u+w(k)); %y=Cx+D+v(k) clear all; close all; ts=0.001; %Continuous Plant a=25;b=133; sys=tf(b,[1,a,0]); dsys=c2d(sy

chap7_8.m

%Kalman filter %x=Ax+B(u+w(k)); %y=Cx+D+v(k) clear all; close all; ts=0.001; M=3000; %Continuous Plant a=25;b=133; sys=tf(b,[1,a,0]); dsys=c2d(sys,ts,'z'); [num,den]=tfdata(dsys,'v');

sonar_anal.m

function sonar_anal(fig) % SONAR_ANAL is a callback for the sonar demo (tof.m). % user data ud=get(fig,'userdata'); ai=ud.ai; ao=ud.ao; h=ud.h; txt=h.text1; % measurement y=getdata(ai);

bc.h

/*********************************** MODULE INFO ************************************ Device : AT90S2333 File name : BC.h Ver nr. : 1.0 Description : Header file fo

initialvalues.java

//: c04:InitialValues.java // From 'Thinking in Java, 2nd ed.' by Bruce Eckel // www.BruceEckel.com. See copyright notice in CopyRight.txt. // Shows default initial values. class Measurement {

kalman.c

/* -*- indent-tabs-mode:T; c-basic-offset:8; tab-width:8; -*- vi: set ts=8: * $Id: kalman.c,v 1.5 2002/02/15 18:11:57 tramm Exp $ * * This is the core Kalman filtering algorithm. * * Author:

chap7_11.m

%Discrete Kalman filter for PID control %Reference kalman_2rank.m %x=Ax+B(u+w(k)); %y=Cx+D+v(k) clear all; close all; ts=0.001; %Continuous Plant a=25;b=133; sys=tf(b,[1,a,0]); dsys=c2d(sy

chap7_9.m

%Kalman filter %x=Ax+B(u+w(k)); %y=Cx+D+v(k) clear all; close all; ts=0.001; M=3000; %Continuous Plant a=25;b=133; sys=tf(b,[1,a,0]); dsys=c2d(sys,ts,'z'); [num,den]=tfdata(dsys,'v');

chap7_10f.m

%Discrete Kalman filter %x=Ax+B(u+w(k)); %y=Cx+D+v(k) function [u]=kalman(u1,u2,u3) persistent A B C D Q R P x yv=u2; if u3==0 x=zeros(2,1); ts=0.001; a=25;b=133; sys=tf(b,[1,a

chap7_10.m

%Discrete Kalman filter for PID control %Reference kalman_2rank.m %x=Ax+B(u+w(k)); %y=Cx+D+v(k) clear all; close all; ts=0.001; %Continuous Plant a=25;b=133; sys=tf(b,[1,a,0]); dsys=c2d(sy