代码搜索：ESTIMATION
找到约 3,786 项符合「ESTIMATION」的源代码
代码结果 3,786
www.eeworm.com/read/264046/11331732
m daropt.m
function [NVR,ALPHA,opts,separ] = daropt(y,p,IRW,method,nvr,alpha,nvr0,alpha0,opts,ALG,output,P0)
% DAROPT Hyper-parameter estimation for DAR
%
% [nvr,alpha,opts,parse]=daropt(y,na,TVP,meth,nvrc,a
www.eeworm.com/read/407580/11414631
m 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
www.eeworm.com/read/407295/11422470
m kf_cwpa_demo.m
% Demonstration for Kalman filter and smoother using a 2D CWPA model
%
% Copyright (C) 2007 Jouni Hartikainen
%
% This software is distributed under the GNU General Public
% Licence (version 2 or lat
www.eeworm.com/read/407295/11422522
kf_cwpa_demoasv
% Demonstration for Kalman filter and smoother using a 2D CWPA model
%
% Copyright (C) 2007 Jouni Hartikainen
%
% This software is distributed under the GNU General Public
% Licence (version 2 or lat
www.eeworm.com/read/407295/11422523
m kf_cwpa_demo.m
% Demonstration for Kalman filter and smoother using a 2D CWPA model
%
% Copyright (C) 2007 Jouni Hartikainen
%
% This software is distributed under the GNU General Public
% Licence (version 2 or lat
www.eeworm.com/read/407295/11422524
asv kf_cwpa_demo.asv
% Demonstration for Kalman filter and smoother using a 2D CWPA model
%
% Copyright (C) 2007 Jouni Hartikainen
%
% This software is distributed under the GNU General Public
% Licence (version 2 or lat
www.eeworm.com/read/400577/11572955
m parzenml3.m
%PARZENML Optimum smoothing parameter in Parzen density estimation.
%
% H = PARZENML(A,FID)
%
% INPUT
% A input dataset
% FID File ID to write progress to (default [], see PRPROGRESS)
%
%
www.eeworm.com/read/347754/11638223
dependencies
../obj/cavlc.o: ../../encoder/cavlc.c ../../common/T264.h ../../common/portab.h \
../../common/config.h ../../encoder/vlc.h ../../common/bitstream.h \
../../encoder/inter.h
../obj/display.o: ../..
www.eeworm.com/read/347288/11676456
cpp stdafx.cpp
// stdafx.cpp : 只包括标准包含文件的源文件
// estimation.pch 将成为预编译头
// stdafx.obj 将包含预编译类型信息
#include "stdafx.h"
// TODO: 在 STDAFX.H 中
//引用任何所需的附加头文件，而不是在此文件中引用
www.eeworm.com/read/155809/11845541
m 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