代码搜索：NetWork

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m contents.m

% ReBEL : Recursive Bayesian Estimation Library - Toolkit % Version 0.2 % % ---CORE ROUTINES--- % % ReBEL Inference System Routines % consistent - Check ReBEL data structures for consisten
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www.eeworm.com/read/485544/6552838

m mlppack.m

function [wh, nodes] = mlppack(W1, B1, W2, B2, W3, B3, W4, B4) % MLPPACK ReBEL MLP neural network weight matrices vectorizer. % % This function packs the parameters (weights and biases) of ReBEL ML
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www.eeworm.com/read/485607/6554717

pro tripplanner.pro

TEMPLATE = app QT += network HEADERS = tripplanner.h SOURCES = main.cpp \ tripplanner.cpp FORMS = tripplanner.ui
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www.eeworm.com/read/485607/6554737

pro tripserver.pro

TEMPLATE = app QT += network HEADERS = clientsocket.h \ tripserver.h SOURCES = clientsocket.cpp \ main.cpp \ tripserver.cpp
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www.eeworm.com/read/485618/6555056

html qsocket.html

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www.eeworm.com/read/483114/6609704

m train.m

function net = train(net, tutor, varargin) % TRAIN % % Train a max-win multi-class support vector classifier network using the % specified tutor to train each component two-class network. %
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m train.m

function net = train(net, tutor, varargin) % TRAIN % % Train a max-win multi-class support vector classifier network using the % specified tutor to train each component two-class network. %
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m train.m

function net = train(net, tutor, varargin) % TRAIN % % Train a dag-svm multi-class support vector classifier network using the % specified tutor to train each component two-class network. %
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www.eeworm.com/read/482893/6615729

h define.h

#ifndef _NET_MONITOR_KERNEL_DEFINE_H_ #define _NET_MONITOR_KERNEL_DEFINE_H_ #include "nb30.h" typedef unsigned char byte; typedef struct _ASTAT_ { ADAPTER_STATUS adapt; NAME_BUFFER
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www.eeworm.com/read/482926/6616270

ob1 tip028.ob1

// Tip028B // 题目： // S7-214与SIMOVERT 电机驱动器之间的自由通信口通信接口 //***概述*** //S7-214通过与一台SIMOVERT微型主电机驱动器通信来起动和停止电机，以及改变输出 //到电机的频率。通信是通过S7-200自由通信口模式进行，使用USS5字协议。输入仿真 //器用来初始化发给电机驱动器的命令。 //***硬件要求** ...
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