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/317326/13505925
m sa_ex7_14.m
% root-Min-Norm AOA estimation for a M = 4 element array with noise variance = .1
% use time averages instead of expected values by assuming ergodicity of the mean and
% ergodicity of the correlati
www.eeworm.com/read/317326/13505960
m sa_ex7_13.m
% root-MUSIC AOA estimation for a M = 6 element array with noise variance = .1
% use time averages instead of expected values by assuming ergodicity of the mean and
% ergodicity of the correlation.
www.eeworm.com/read/314385/13568714
m demo2_02.m
%
% Demonstrates relative performance of Wiener filter (fixed-gain)
% and Kalman filter (time-varying gain) on random walk estimation
%
% Applied to random walk process with gaussian sampling nois
www.eeworm.com/read/314385/13568717
m rtsvskf.m
%
% Demonstrates relative performance of Kalman filter
% and Rauch-Tung-Striebel smoother on random walk estimation
%
clear all;
close all;
N = 100; % Number of samples of process used in simul
www.eeworm.com/read/307094/13729193
m mafi_sch_new.m
function [Y, Rhh] = mafi_sch_new(r,Lh,T_SEQ,OSR)
%
% MAFI: This function performes the tasks of channel impulse
% respons estimation, bit syncronization, matched
%
www.eeworm.com/read/307094/13729197
m mafi_sch.m
function [Y, Rhh] = mafi_SCH(r,Lh,T_SEQ,OSR)
%
% MAFI: This function performes the tasks of channel impulse
% respons estimation, bit syncronization, matched
% filtering a
www.eeworm.com/read/306970/13734464
c motion_est_mmx.c
/*
* MMX optimized motion estimation
* Copyright (c) 2001 Fabrice Bellard.
* Copyright (c) 2002-2004 Michael Niedermayer
*
* mostly by Michael Niedermayer
*
* This fil
www.eeworm.com/read/300891/13883417
m kernel.m
function f = kernel(xa,x,h);
%KERNEL: Density (1D) estimation using a Gaussian Kernel
% Density Estimator. This is used to compute the plugin
% estimators of entropy
%
% Silverman,
www.eeworm.com/read/136827/5847395
c motion_est.c
/*
* Motion estimation
* Copyright (c) 2000,2001 Fabrice Bellard.
* Copyright (c) 2002-2003 Michael Niedermayer
*
*
* This library is free software; you can redistribute it and/or
* modify it
www.eeworm.com/read/331502/6327352
m matul.m
function [hest] = matul (bisp)
%MATUL Impulse response estimation using Matsuoka-Ulrych algorithm
% hest = matul(bisp)
% bisp - the estimated bispectrum
% (e.g., as computed by bispecd or