代码搜索：Neuron
找到约 763 项符合「Neuron」的源代码
代码结果 763
www.eeworm.com/read/248950/12531165
m train.m
function w = train ( w , L , eta , alpha )
# train ( w , L , eta , alpha )
# trains a single neuron from weight vector w
# using global data in x,t
# fo
www.eeworm.com/read/453796/7412287
java javamlp.java
/*
MLP neural network in Java
by Phil Brierley
www.philbrierley.com
This code may be freely used and modified at will
Tanh hidden neurons
Linear output neuron
To include an input bias create an
ext
www.eeworm.com/read/187736/5217716
java architecture.java
package net.openai.ai.nn.architecture;
import net.openai.ai.nn.network.*;
/**
* This class defines how the neural network will be constructed
* or connected. How each neuron will be connected
www.eeworm.com/read/315543/3619645
h recurrentneuron.h
#ifndef _RECURRENTNEURON_H
#define _RECURRENTNEURON_H
#include "SimpleNeuron.h"
#include "defines.h"
#include
namespace annie
{
/** A neuron used for recurrent networks.
* These neurons
www.eeworm.com/read/276537/10731495
m linear304.m
%% Linear Fit of Nonlinear Problem
% A linear neuron is trained to find the minimum sum-squared error linear fit to
% a nonlinear input/output problem.
%
% Copyright 1992-2002 The MathWorks, Inc.
www.eeworm.com/read/458769/7289626
txt nnfunctions.txt
/*Aim:- Write a program in Lisp to demonstrate working of an artificial neuron. (Enter an input vector X and weight vector W. Calculate weighted sum XW. Transform this using signal or activation fun
www.eeworm.com/read/259886/11759585
m demop5.m
%% Normalized Perceptron Rule
% A 2-input hard limit neuron is trained to classify 5 input vectors into two
% categories. Despite the fact that one input vector is much bigger than the
% others, t
www.eeworm.com/read/259886/11759833
m demolin4.m
%% Linear Fit of Nonlinear Problem
% A linear neuron is trained to find the minimum sum-squared error linear fit to
% a nonlinear input/output problem.
%
% Copyright 1992-2002 The MathWorks, Inc.
www.eeworm.com/read/152094/12139962
m linear304.m
%% Linear Fit of Nonlinear Problem
% A linear neuron is trained to find the minimum sum-squared error linear fit to
% a nonlinear input/output problem.
%
% Copyright 1992-2002 The MathWorks, Inc.
www.eeworm.com/read/431675/8662419
m randnr.m
function w = randnr(s,r)
%RANDNR Normalized row random generator.
%
% RANDNR(S,R)
% S - Size of neuron layer (# of rows).
% R - Number of inputs (# of columns).
% Returns an SxR weight matrix.
%