代码搜索:ESTIMATION
找到约 3,786 项符合「ESTIMATION」的源代码
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www.eeworm.com/read/344583/11871621
m cp0803_rakeselector.m
% FUNCTION 8.11 : "cp0803_rakeselector"
%
% Simulates channel estimation for a discrete-time channel
% impulse response 'hf' with time resolution 'ts' in
% seconds. In addition, the function eva
www.eeworm.com/read/252894/12258604
c motion_est.c
/*
* Motion estimation
* Copyright (c) 2000,2001 Fabrice Bellard.
* Copyright (c) 2002-2004 Michael Niedermayer
*
*
* This library is free software; you can redistribute it and/or
* modify it
www.eeworm.com/read/234324/14115869
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
www.eeworm.com/read/233013/14173842
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/228513/14381021
m cp0803_rakeselector.m
% FUNCTION 8.11 : "cp0803_rakeselector"
%
% Simulates channel estimation for a discrete-time channel
% impulse response 'hf' with time resolution 'ts' in
% seconds. In addition, the function eva
www.eeworm.com/read/218840/14904585
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
www.eeworm.com/read/216698/14997351
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
www.eeworm.com/read/206661/15292441
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
www.eeworm.com/read/471707/1425682
c motion_est_mmx.c
/*
* MMX optimized motion estimation
* Copyright (c) 2001 Fabrice Bellard.
* Copyright (c) 2002-2004 Michael Niedermayer
*
* This library is free software; you can redistribute it and/or
* modif
www.eeworm.com/read/457216/1599677
m ml_covariance_est.m
% Section 7.1.1: Covariance estimation for Gaussian variables
% Boyd & Vandenberghe "Convex Optimization"
% Joëlle Skaf - 04/24/08
%
% Suppose y \in\reals^n is a Gaussian random variable with zero