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找到约 5,352 项符合「Learning」的源代码

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m contents.m

% Unsupervised statistical learning methods. % % unsudemo - Demo of unsupervised learning methods for 2D feature space. % % mln - Compute value of logarihm of the likelihood function.
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www.eeworm.com/read/367442/9748281

m~ contents.m~

% Statistical Pattern Recognition Toolbox. % % Contents % % bayes - (dir) Bayes classification. % datasets - (dir) Functions for handling with data sets. % generalp - (dir) General purpose
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www.eeworm.com/read/170936/9779377

m somtrain.m

function net = somtrain(net, options, x) %SOMTRAIN Kohonen training algorithm for SOM. % % Description % NET = SOMTRAIN{NET, OPTIONS, X) uses Kohonen's algorithm to train a % SOM. Both on-line and ba
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www.eeworm.com/read/415313/11076690

m somtrain.m

function net = somtrain(net, options, x) %SOMTRAIN Kohonen training algorithm for SOM. % % Description % NET = SOMTRAIN{NET, OPTIONS, X) uses Kohonen's algorithm to train a % SOM. Both on-line and ba
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www.eeworm.com/read/413912/11137386

m somtrain.m

function net = somtrain(net, options, x) %SOMTRAIN Kohonen training algorithm for SOM. % % Description % NET = SOMTRAIN{NET, OPTIONS, X) uses Kohonen's algorithm to train a % SOM. Both on-line and ba
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www.eeworm.com/read/248950/12531165

m train.m

function w = train ( w , L , eta , alpha ) # train ( w , L , eta , alpha ) # trains a single neuron from weight vector w # using global data in x,t # fo
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m learn.m

function wret = learn ( w , L ) # learning for single neuron classifier # I don't understand why this is invisible global x ; global t ; disp (" enter learn ") for l = 1:L a = x * w ; y =
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www.eeworm.com/read/190969/8435853

m mytraining.m

function [w,error ]= mytraining(x,h,gaussian,learning,mode,center,variance) % [fnum dnum]= size(gaussian); w = rand(fnum,1)*2-1; oldw=w; for i=1:100 % 100 epoches for j=1:dn
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www.eeworm.com/read/290144/8502206

m contents.m

% Neural Network Design Demonstrations. % Copyright (c) 1994 by PWS Publishing Company. % % General % nnd - Splash screen. % nndtoc - Table of contents. % nnsound - Turn Neural Net
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www.eeworm.com/read/289487/8548648

m rncalc.m

function [c,d]=rncalc(xapp,yapp,kernel,kerneloption,lambda,T) % USAGE % % [c,d]=rncalc(xapp,app,kernel,kerneloption,lambda,T); % % % y= K*c+ T*d % calculates the minimizer of
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