代码搜索：patterns
找到约 8,017 项符合「patterns」的源代码
代码结果 8,017
www.eeworm.com/read/385990/8772986
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 Lesser General
www.eeworm.com/read/283821/8986860
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/283821/8986904
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/281874/9128128
cpp waptree.cpp
/*
This is the WAP algorithm program based on the description in:
Jian Pei, Jiawei Han, Behzad Mortazavi-asl, and Hua Zhu, "Mining Access
Patterns Eciently from Web Logs", PAKDD 2000.
1.Development
www.eeworm.com/read/281648/9145248
h resource.h
//{{NO_DEPENDENCIES}}
// Microsoft Visual C++ generated include file.
// Used by Patterns.rc
//
#define IDM_ABOUTBOX 0x0010
#define IDD_ABOUTBOX 100
#define
www.eeworm.com/read/183443/9158851
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/183443/9158983
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/183443/9158988
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/181389/9256470
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/181389/9256565
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