代码搜索:patterns

找到约 8,017 项符合「patterns」的源代码

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www.eeworm.com/read/351797/10609695

m fwd.m

function y = fwd(net,x) % FWD % % Compute the output of a multi-class support vector classification network. % % y = fwd(net, x); % % where x is a matrix of input patterns, where each colu
www.eeworm.com/read/351797/10609862

m fwd.m

function y = fwd(net,x) % FWD % % Compute the output of a multi-class support vector classification network. % % y = fwd(net, x); % % where x is a matrix of input patterns, where each colu
www.eeworm.com/read/351797/10609876

m fwd.m

function y = fwd(net, x) % FWD % % Compute the output of a dag-svm multi-class support vector classification % network. % % y = fwd(net, x); % % where x is a matrix of input patterns, in
www.eeworm.com/read/348907/10860448

changelog

2006-06-10 meld-1.1.4 ===================== * Refresh and reload buttons. * Better context menu behaviour for vcview. * Allow escaping of shell patterns. (Patch from Jared Sulem) * Stop button
www.eeworm.com/read/419563/10860757

txt fig3_53.m .txt

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Figure 3.53 % Beam patterns: N = 11 % (a) u-space % (b) theta-space % Xin Zhang 4/9/99 % last updated 9/5/00 by K. Bell % Lillian Xu
www.eeworm.com/read/273047/10930340

m fwd.m

function y = fwd(net, x) % FWD % % Compute the output of a dag-svm multi-class support vector classification % network. % % y = fwd(net, x); % % where x is a matrix of input patterns, in
www.eeworm.com/read/453434/7420740

m fig3_53.m

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% % Figure 3.53 % Beam patterns: N = 11 % (a) u-space % (b) theta-space % Xin Zhang 4/9/99 % last updated 9/5/00 by K. Bell % Lillian Xu
www.eeworm.com/read/437397/7749147

c exercise.c

/* Exercise an RS codec a specified number of times using random * data and error patterns * * Copyright 2002 Phil Karn, KA9Q * May be used under the terms of the GNU General Public License (GPL)
www.eeworm.com/read/437397/7749157

c rstest.c

/* Test the Reed-Solomon codecs * for various block sizes and with random data and random error patterns * * Copyright 2002 Phil Karn, KA9Q * May be used under the terms of the GNU General Public
www.eeworm.com/read/398324/7994152

m fwd.m

function y = fwd(net,x) % FWD % % Compute the output of a multi-class support vector classification network. % % y = fwd(net, x); % % where x is a matrix of input patterns, where each colu