代码搜索：Matrix
找到约 10,000 项符合「Matrix」的源代码
代码结果 10,000
www.eeworm.com/read/278885/10492111
java covariance.java
/**
* file: Covariance.java
*
* Last editted: Ryan Irwin
*
*/
// import necessary java libraries
//
//These imports are not needed - Phil T. 6-23-03
//import java.awt.*;
//import java.applet.
www.eeworm.com/read/278885/10492230
java,v covariance.java,v
head 1.3;
access;
symbols;
locks; strict;
comment @# @;
1.3
date 2005.05.23.21.05.54; author rirwin; state Exp;
branches;
next 1.2;
1.2
date 2005.03.09.21.21.11; author patil; state Exp;
branches;
www.eeworm.com/read/278885/10492450
java eigen.java
/**
* file: Eigen.java
*
* last edited: Ryan Irwin
*
*/
// import necessary java libraries
//
//These imports are not needed - Phil T. 6-23-03
//import java.awt.*;
//import java.applet.*;
//imp
www.eeworm.com/read/352895/10495150
py analyse_file.py
#! /usr/bin/env python
import os
import sys
#
#
#
#zc030x Register map
#-------------------
#0x01d to 0x020 HSYNC/VSYNC (same values as hv7131b)
#0x090 to 0x094: i2c bus control
#0x10a to 0x112: A 3
www.eeworm.com/read/424063/10499464
m dlqew.m
function [l,m,p,e] = dlqew(a,g,c,j,q,r)
%DLQEW Discrete linear quadratic estimator design for the system:
% x[n+1] = Ax[n] + Bu[n] + Gw[n] {State equation}
% z[n] = Cx[n] + Du[n] + Jw
www.eeworm.com/read/424063/10499772
m lqe.m
function [l,p,e] = lqe(a,g,c,q,r,t)
%LQE Linear quadratic estimator design. For the continuous-time system:
% .
% x = Ax + Bu + Gw {State equation}
% z = Cx + Du + v {Mea
www.eeworm.com/read/424063/10499945
m lqed.m
function [l,m,p,e] = lqed(a,g,c,q,r,Ts)
%LQED Discrete linear quadratic estimator design from continuous
% cost function.
% [L,M,P,E] = LQED(A,G,C,Q,R,Ts) calculates the Kalman gain matrix
www.eeworm.com/read/424063/10500000
m dlqe.m
function [l,m,p,e] = dlqe(a,g,c,q,r,t)
%DLQE Discrete linear quadratic estimator design for the system:
% x[n+1] = Ax[n] + Bu[n] + Gw[n] {State equation}
% z[n] = Cx[n] + Du[n] + v[n] {Mea
www.eeworm.com/read/424063/10500267
m ss_tbl31.m
Gold sequences for the table of problem 3.1 of Spread Spectrum Chapter
Note that the sequences are the columns of the below matrix not the rows,
so we have to take the transpose of the following m