代码搜索：Estimation

找到约 3,786 项符合「Estimation」的源代码

代码结果 3,786
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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
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www.eeworm.com/read/490601/6449470

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
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www.eeworm.com/read/488312/6492157

m rls.m

% RLS Algorithm randn('seed', 0) ; rand('seed', 0) ; NoOfData = 8000 ; % Set no of data points used for training Order = 32 ; % Set the adaptive filter order Lambda = 0.98 ; % Set the
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www.eeworm.com/read/488224/6498638

m program_15_4.m

% Program 15_4 % Power Spectrum Estimation Using Welch's Method % n = 0:1000; g = 2*sin(0.12*pi*n) + sin(0.28*pi*n) + randn(size(n)); nfft = input('Type in the fft size = '); window = hamming(25
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www.eeworm.com/read/485544/6552813

readme

-- ReBEL : Recursive Bayesian Estimation Library -- A Matlab toolkit for Recursive Bayesian Estimation Copyright 2002, Rudolph van der Merwe 1) WHAT IS ReBEL ? Re
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www.eeworm.com/read/484955/6569523

m rls_demo.m

% RLS Algorithm randn('seed', 0) ; rand('seed', 0) ; NoOfData = 8000 ; % Set no of data points used for training Order = 32 ; % Set the adaptive filter order Lambda = 0.98 ; % Set the forgetting
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www.eeworm.com/read/484955/6569528

m nlms_demo.m

% Normalized LMS Algorithm randn('seed', 0) ; rand('seed', 0) ; NoOfData = 8000 ; % Set no of data points used for training Order = 32 ; % Set the adaptive filter order Mu = 1.0 ; % Set the step
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www.eeworm.com/read/479088/6699287

m weibmen.m

function [bh,ah] = weibmen(x); % % Estimation of Weibull parameters using the % method of Menon. % [m n] = size(x); leng=length(x); if m ~= leng temp=m; m = n; n = temp
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www.eeworm.com/read/476539/6755735

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
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www.eeworm.com/read/264746/11302989

m ncoeff2.m

% % Bandpass filter length estimation % Ncoeff2.m Problem 7.5, p426. % df=3/96; dp=0.00115; ds=0.0001; b1=0.01202; b2=0.09664; b3=-0.51325; b4=0.00203; b5=-0.5705; b6=-0.44314; t1=log10(dp);
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