代码搜索:ESTIMATION

找到约 3,786 项符合「ESTIMATION」的源代码

代码结果 3,786
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m torr_errh.m

% By Philip Torr 2002 % copyright Microsoft Corp. % % %designed for the good of the world by Philip Torr % copyright Philip Torr and Microsoft Corp 2002 % linear estimation of H %this uses
www.eeworm.com/read/159560/10639839

m torr_mapsac_h.m

% By Philip Torr 2002 % copyright Microsoft Corp. % % %designed for the good of the world by Philip Torr % copyright Philip Torr and Microsoft Corp 2002 % linear estimation of H % % @article
www.eeworm.com/read/159560/10639851

m torr_napsac_h.m

% By Philip Torr 2002 % copyright Microsoft Corp. % % %designed for the good of the world by Philip Torr % copyright Philip Torr and Microsoft Corp 2002 % linear estimation of H % % @article
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m torr_errh.m

% By Philip Torr 2002 % copyright Microsoft Corp. % % %designed for the good of the world by Philip Torr % copyright Philip Torr and Microsoft Corp 2002 % linear estimation of H %this uses
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m example2.m

% % This Matlab script provides an interactive way to reproduce % Example 2: Variance estimation reported in: % Zoubir, A.M. and Boashash, B. The Bootstrap and Its Application in % Signal Proce
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m cc_mvgarch_full_likelihood.m

function [logL, likelihoods]=cc_mvgarch_full_likelihood(parameters, data, archP,garchQ); % PURPOSE: % Full likelihood for use in the CC_MVGARCH estimation and % returns the likelihood
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m calcinfoloss.m

function [InfoLoss] = CalcInfoLoss(D, N, Crossval_OR_Resubstit) % The Estimation of Information Loss can be found in the PAMI paper % Copyright: Dimitrios Ververidis % Version 0.0 Date: 09
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m call_lam.m

% M-file for call of the LAMBDA routines for integer estimation of the % GPS double difference ambiguities % disall squared norms \hat{a}-\check{a} (of candidates inside ellipsoid) % n dimensi
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txt changes.txt

Changes in Version JM 10.2 (since JM 10.1) ------------------------------------------ - encoder: fast subpixel motion estimation for EPZS [JVT-Q079] (AT) - encoder: SI picture implementation (ES)
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m cc_mvgarch_full_likelihood.m

function [logL, likelihoods]=cc_mvgarch_full_likelihood(parameters, data, archP,garchQ); % PURPOSE: % Full likelihood for use in the CC_MVGARCH estimation and % returns the likelihood