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/384673/2598547
m wt04fig22.m
%CAPTION
fprintf('\n');
disp('Figure 4.22')
disp('Window 1: Realization of a locally stationary process.')
disp('Window 2: Estimation of the Wigner-Ville spectrum calculated by')
disp('averaging
www.eeworm.com/read/373026/2767610
m contents.m
% Chapter 7: Statistical estimation
%
% probbounds.m - Section 7.4.3: Probability bounds example with Voronoi diagram
% expdesign.m - Section 7.5.2: Experiment design
% logistics.m - Figure
www.eeworm.com/read/364434/2906154
svn-base motion_est_mmx.c.svn-base
/*
* MMX optimized motion estimation
* Copyright (c) 2001 Fabrice Bellard.
* Copyright (c) 2002-2004 Michael Niedermayer
*
* mostly by Michael Niedermayer
*
* This file is pa
www.eeworm.com/read/474600/6813487
m bayesian_parameter_est.m
function [mu, sigma] = Bayesian_parameter_est(train_patterns, train_targets, sigma)
% Estimate the mean using the Bayesian parameter estimation for Gaussian mixture algorithm
% Inputs:
% pattern
www.eeworm.com/read/359187/6841978
m bayesian_parameter_est.m
function [mu, sigma] = Bayesian_parameter_est(train_features, train_targets, sigma, region)
% Estimate the mean using the Bayesian parameter estimation for Gaussian mixture algorithm
% Inputs:
%
www.eeworm.com/read/294132/8250825
m mafi_sch.m
function [Y, Rhh] = mafi_sch(r,L,T_SEQ,OSR)
%
% MAFI: This function performes the tasks of channel impulse
% respons estimation, bit syncronization, matched
% filtering and si
www.eeworm.com/read/393424/8287956
m sde_library_run.m
% Main model-library routine: simulation, numerical solution and parameter estimation of Ito and Stratonovich SDEs.
%
% usage: SDE_library_run;
% Copyright (C) 2007, Umberto Picchini
% umberto
www.eeworm.com/read/415311/11077137
m bayesian_parameter_est.m
function [mu, sigma] = Bayesian_parameter_est(train_features, train_targets, sigma, region)
% Estimate the mean using the Bayesian parameter estimation for Gaussian mixture algorithm
% Inputs:
%
www.eeworm.com/read/415086/11084417
m em.m
% Mixture-of-Gaussian density estimation with the Expectation Maximization algorithm.
%
% Inputs:
% - x: a DxN matrix of N data points in a D-dimensional space
% - p: a vector of K initial mix
www.eeworm.com/read/205039/15327849
m deltaparametri.m
function [dvar] = deltaparametri(delta,dev,cor,legame,valuta,cambi,vm)
%DELTAPARAMETRI deltavar estimation changing the parameters.
%
% [dvar] = deltaparametri(delta,dev,cor,legame,valuta,cambi,vm)
%