代码搜索:MLP

找到约 754 项符合「MLP」的源代码

代码结果 754
www.eeworm.com/read/192078/8408277

m mlp.m

%MLP Multilayer Perceptron algorithm % % 'ifile.mat' - input file containing: % Nr - members of ensemble % dim - iterations % Nneur - number of neurons % Sx - standard deviation
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m mlp.m

clear,clc,close all % MATLAB neural network back propagation code % by AliReza KashaniPour & Phil Brierley % first version 29 March 2006 % 2's edition 14 agust 2007 % % This code implements the
www.eeworm.com/read/429878/8783800

htm mlp.htm

Netlab Reference Manual mlp mlp Purpose Create a 2-layer feedforward network. Synopsis net = mlp(nin, nhidden,
www.eeworm.com/read/182174/9213577

m mlp.m

function y = mlp(x,theta,s1,s2); % PURPOSE : To simulate a one hidden layer sigmoidal MLP. % INPUTS : - x = The network input. % - theta = The network weights. % - s1 = Number of
www.eeworm.com/read/177674/9442444

m mlp.m

function net = mlp(nin, nhidden, nout, outfunc, prior, beta) %MLP Create a 2-layer feedforward network. % % Description % NET = MLP(NIN, NHIDDEN, NOUT, FUNC) takes the number of inputs, % hidden units
www.eeworm.com/read/176823/9483146

m mlp.m

function net = mlp(nin, nhidden, nout, outfunc, prior, beta) %MLP Create a 2-layer feedforward network. % % Description % NET = MLP(NIN, NHIDDEN, NOUT, FUNC) takes the number of inputs, % hidden units
www.eeworm.com/read/162605/10291563

m mlp.m

clc; clear all; InputFilename = 'aa.wav'; %change it according to your wave files [inspeech, Fs, bits] = wavread(InputFilename); % read the wavefile Order = 10; % order of the model used b
www.eeworm.com/read/425546/10349016

m mlp.m

function net = mlp(nin, nhidden, nout, outfunc, prior, beta) %MLP Create a 2-layer feedforward network. % % Description % NET = MLP(NIN, NHIDDEN, NOUT, FUNC) takes the number of inputs, % hidden
www.eeworm.com/read/161821/10367371

mlp newtrainedmlp.mlp

3 10 1 -0.588524965172076 0.716651831106038 0.409652759522463 -0.18556380508436 0.0887570131413128 -0.488390602655531 -0.745995651084505 -0.547004454098551 -0.872806470119664 -0.935633744239792
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mlp trainedbarrelanglemlp.mlp

3 10 1 -0.588524965172076 0.716651831106038 0.409652759522463 -0.18556380508436 0.0887570131413128 -0.488390602655531 -0.745995651084505 -0.547004454098551 -0.872806470119664 -0.935633744239792