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Measurement 的代码
auto_baud_with_tracking.v
//-----------------------------------------------------------------------------
// Auto Baud with tracking core
//
// This file is part of the "auto_baud" project.
// http://www.opencores.org/
//
add_observation_noise.m
function z= add_observation_noise(z,R, addnoise)
%function z= add_observation_noise(z,R, addnoise)
%
% Add random measurement noise. We assume R is diagonal.
if addnoise == 1
len= size(
add_observation_noise.m
function z= add_observation_noise(z,R, addnoise)
%function z= add_observation_noise(z,R, addnoise)
%
% Add random measurement noise. We assume R is diagonal.
if addnoise == 1
len= size(
auto_baud_with_tracking.v
//-----------------------------------------------------------------------------
// Auto Baud with tracking core
//
// This file is part of the "auto_baud" project.
// http://www.opencores.org/
//
auto_baud.v
//-----------------------------------------------------------------------------
// Auto Baud core
//
// This file is part of the "auto_baud" project.
// http://www.opencores.org/
//
//
// Desc
weighted_impulsive_iterative_huber_m_nlos.m
% NLOS mitigation based on Huber M estimation
% 2007.3.18
% written by Tang Hong
% IEEE Trans. On signal processing,vol47,No.4, 1999
% " robust Huber adaptive filter"
% clc;
clear;
impulsive_iterative_huber_m_nlos.m
% NLOS mitigation based on Huber M estimation
% 2007.3.18
% written by Tang Hong
% IEEE Trans. On signal processing,vol47,No.4, 1999
% " robust Huber adaptive filter"
% clc;
clear;
impulsive_iterative_huber_m_nlos.asv
% NLOS mitigation based on Huber M estimation
% 2007.3.18
% written by Tang Hong
% IEEE Trans. On signal processing,vol47,No.4, 1999
% " robust Huber adaptive filter"
% clc;
clear;
weighted_impulsive_iterative_huber_m_nlos.asv
% NLOS mitigation based on Huber M estimation
% 2007.3.18
% written by Tang Hong
% IEEE Trans. On signal processing,vol47,No.4, 1999
% " robust Huber adaptive filter"
% clc;
clear;
l_gu.m
function units=l_gu(wlog,mnem)
% Get units of measurement of curve with mnemonic "mnem" from log data set "wlog"
% If S4M.case_sensitive is set to false, the case of the curve mnemonic is disregarded.