代码搜索：NetWork

找到约 10,000 项符合「NetWork」的源代码

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热门代码： main.c GPIO I2C SPI UART timer interrupt ADC PWM LED
www.eeworm.com/read/220696/14791587

m grmincutset.m

function [nMCS,mf]=grMinCutSet(E,s,t) % Function [nMCS,mf]=grMinCutSet(E,s,t) find the first % minimal cut-sets of the network. % Input parameters: % E(m,2) or (m,3) - the arrows of digraph an
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www.eeworm.com/read/220636/14794552

m demopsonet.m

% demoPSOnet.m % script to show a quick, uncomplicated demo of using trainpso for training % a neural net % % tries to build a feedforward neural net to approximate a noisy increaing % sin funct
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www.eeworm.com/read/119783/14822533

c telnet.c

/* Internet Telnet client */ #include #ifdef __TURBOC__ #include #include #endif #include "global.h" #include "mbuf.h" #include "socket.h" #include "telnet.h" #i
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www.eeworm.com/read/119503/14827704

boost readme.boost

A collection of Matlab scripts to boost a Matlab neural network Requires Matlab Neural Network toolbox. Script P450bskel.m reads data files (not supplied) and the calls other scripts to perform boost
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www.eeworm.com/read/119269/14835684

c winnet.c

/* * Windows networking abstraction. * * Due to this clean abstraction it was possible * to easily implement IPv6 support :) * * IPv6 patch 1 (27 October 2000) Jeroen Massar
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www.eeworm.com/read/220289/14843736

m mdnpak.m

function w = mdnpak(net) %MDNPAK Combines weights and biases into one weights vector. % % Description % W = MDNPAK(NET) takes a mixture density network data structure NET % and combines the network w
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www.eeworm.com/read/220289/14843738

m demolgd1.m

%DEMOLGD1 Demonstrate simple MLP optimisation with on-line gradient descent % % Description % The problem consists of one input variable X and one target variable % T with data generated by sampling X
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www.eeworm.com/read/220289/14843790

m nethess.m

function [h, varargout] = nethess(w, net, x, t, varargin) %NETHESS Evaluate network Hessian % % Description % % H = NETHESS(W, NET, X, T) takes a weight vector W and a network data % structure NET, to
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www.eeworm.com/read/220289/14843831

m mlpfwd.m

function [y, z, a] = mlpfwd(net, x) %MLPFWD Forward propagation through 2-layer network. % % Description % Y = MLPFWD(NET, X) takes a network data structure NET together with a % matrix X of input vec
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www.eeworm.com/read/220289/14843845

m mdn.m

function net = mdn(nin, nhidden, ncentres, dim_target, mix_type, ... prior, beta) %MDN Creates a Mixture Density Network with specified architecture. % % Description % NET = MDN(NIN, NHIDDEN, NCENTRE
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