Parzen窗 源代码

d = 2; M = 3; Q = 4; T = 5; Sigma = 10; N = sample_discrete(normalize(ones(1,M)), 1, Q); data = randn(d,T); mu = randn(d,M,Q); …

function D = parzen(train_features, train_targets, hn, region) % Classify using the Parzen windows algorithm % Inputs: % fea…

%利用Parzen窗法对总体概率密度函数进行估计 %窗函数选择正态窗函数 %课本140页，利用样本估计正态函数概密 clear all;clc; %--------------------------1024点---------------------…

function test_targets = parzen(train_patterns, train_targets, test_patterns, hn) % Classify using the Parzen windows algorithm …

N = 64;L2 = 15; L3 = 10;delt3 = 1/L3; a1 = 0.8;a2 = 0.6; %f1 = 0.2;f2 = 0.3; w1 = 2*pi*f1;w2 = 2*pi*f2; %for k = 1:N % X…

d = 2; M = 3; Q = 4; T = 5; Sigma = 10; N = sample_discrete(normalize(ones(1,M)), 1, Q); data = randn(d,T); mu = randn(d,M,Q); [B…

%PARZEN_DD Parzen data description. % % W = parzen_dd(A,fracrej) % % Fit a Parzen density on dataset A. The threshold is p…

function test_targets = parzen(train_patterns, train_targets, test_patterns, hn) % Classify using the Parzen windows algorithm …

function test_targets = parzen(train_patterns, train_targets, test_patterns, hn) % Classify using the Parzen windows algorithm …

function test_targets = parzen(train_patterns, train_targets, test_patterns, hn) % Classify using the Parzen windows algorithm …