代码搜索：ESTIMATION
找到约 3,786 项符合「ESTIMATION」的源代码
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www.eeworm.com/read/258606/11850875
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/256799/11971853
m parzenml.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/255755/12057875
m parzenml.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/341517/12080386
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/254742/12121135
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
www.eeworm.com/read/152166/12135110
rpt signal.pow.rpt
PowerPlay Power Analyzer report for signal
Sat Mar 18 23:38:49 2006
Version 5.0 Build 148 04/26/2005 SJ Full Version
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; Table of Contents ;
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1. Le
www.eeworm.com/read/253950/12174094
htm evidence.htm
Netlab Reference Manual evidence
evidence
Purpose
Re-estimate hyperparameters using evidence approximation.
Synopsis
www.eeworm.com/read/150905/12249100
m parzenml.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/150905/12250255
htm evidence.htm
Netlab Reference Manual evidence
evidence
Purpose
Re-estimate hyperparameters using evidence approximation.
Synopsis