代码搜索:ESTIMATION

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www.eeworm.com/read/150760/12265478

html contents.html

Contents.m
www.eeworm.com/read/150760/12266173

m contents.m

% Probability distribution functions. % % estimation - (dir) Probability distribution estimation. % % dsamp - Generates samples from discrete distribution. % erfc2 - Normal cumulative dis
www.eeworm.com/read/251528/12339550

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/149739/12353465

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/148489/12463381

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/231449/14233594

m program_11_4.m

% Program 11_4 % Power Spectrum Estimation Using Welch's Method % colordef black 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 = '); win
www.eeworm.com/read/227046/14442791

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/225665/14526573

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/124397/14569794

m lpcgain.m

function G = lpcgain(xi,P) % lpcgain --> Gain estimation from prediction error energy. % % % G = lpcgain(xi,P) % % % The gain across speech frames, returned in vector
www.eeworm.com/read/222611/14683598

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