代码搜索：ESTIMATION
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www.eeworm.com/read/149739/12352758
m testk.m
%TESTK Error estimation of the K-NN rule
%
% E = TESTK(A,K,T)
%
% INPUT
% A Training dataset
% K Number of nearest neighbors (default 1)
% T Test dataset (default [], i.e. find leave-one-out e
www.eeworm.com/read/222974/14666689
cc bfgsmap.cc
#include
#include
namespace {
using namespace amis;
BFGSMAPLauncherItem< BFGSMAP< BinaryFeature > > bfgs_binary( "BFGSMAP", "Amis", "binary", "Limi
www.eeworm.com/read/218840/14904458
m hosademo.m
function hosademo
%HOSADEMO Demonstrates some of the capabilities of the HOSA Toolbox
% hosademo
%
% HOSADEMO presents a menu of demos.
% The HOSA Toolbox offers several routines for
%
www.eeworm.com/read/214554/15096253
m change_domain.m
function [channel_estimation]=change_domain(channel_post_ti)
www.eeworm.com/read/213492/15133823
m contents.m
% Probability distribution estimation.
%
% emgmm - Expectation-Maximization Algorithm for GMM.
% melgmm - Maximizes Expectation of Log-Likelihood for Gaussian mixture.
% mlcgmm - Maximal Li
www.eeworm.com/read/213492/15133831
m~ contents.m~
% Probability distribution estimation.
%
% emgmm - Expectation-Maximization Algorithm for GMM.
% melgmm - Maximizes Expectation of Log-Likelihood for Gaussian mixture.
% mlcgmm - Maximal Li
www.eeworm.com/read/411674/11233976
m contents.m
% Probability distribution estimation.
%
% emgmm - Expectation-Maximization Algorithm for GMM.
% melgmm - Maximizes Expectation of Log-Likelihood for Gaussian mixture.
% mlcgmm - Maximal Li
www.eeworm.com/read/205039/15327852
m contents.m
% Value at Risk.
%
% Data analisys.
% rendimenti - prices to returns.
% semplicecorr - correlation between risk factors and assets (normal method).
% ewmacorr - correlation bet
www.eeworm.com/read/200271/15436029
m blind3sub.m
% subspace method for blind channel estimation
%
%
echoF=1; % turn on/off output display
dB=15;
T=1000; % sample amount
L=4; M=4; N=5; % L: antenna #. M: channel length. N: smoothing.
d=M+N;
www.eeworm.com/read/200269/15436033
m blindsub.m
% subspace method for blind channel estimation
%
%
echoF=1; % turn on/off output display
dB=15;
T=1000; % sample amount
L=4; M=4; N=5; % L: antenna #. M: channel length. N: smoothing.
d=M+N;