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用人工神经网络实现异或的功能。用反向传播算法（BP）来实现神经网络，正确率可以达到80% -using artificial neural network XOR functions. With back-propagation algorithm (BP) to achieve neural network, can achieve an accuracy rate of 80%
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用c语言实现的bp神经网络实现异或功能，比较好用
-use the C Language bp neural network XOR functions, better quality
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在matlab环境下，利用bp神经网络实现异或分类问题,In the matlab environment, the use of bp neural network XOR classification problem
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利用三层BP人工神经网络解决异或问题（XOR）用matlab编程实现，网络结构可以方便地调整-The use of three BP artificial neural network to solve XOR problem (XOR) using matlab programming, the network structure can be easily adjusted
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用人工神经网络的bp的方法解决异或问题-Using artificial neural network bp means to solve the XOR problem
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自己写的一个简单的神经网络(BP)算法，用来解决异或（XOR)问题,初学神经网络的人可以下来看！-Wrote it myself a simple neural network (BP) algorithm, to solve the exclusive-OR (XOR) problem, learning neural network can look at the next!
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测试神经网络异或问题，只是一个很小的程序，希望大家能多多指教。-Testing neural network XOR problem, only a small fraction of the procedure, I hope we can all the exhibitions.
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Make a program to train a Backpropagation neural network which simulates the behavior of an XOR gate.
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code for XOR problem using BP neural network without using matlabtoolbox
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对于bp神经网络具体算法的编程实现
没有使用自带的神经网络包
可以更好的了解bp算法的内部实现-Specific algorithm for bp neural network programming to achieve without using neural network package that comes with better understanding of the internal implementation bp algorithm
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neural network back-progate to solve xor question,
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VC++实现BP前向神经网络异或算法，（非常好）-VC++ to achieve BP XOR forward neural network algorithm (very good)
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matlab语言编写的基于BP神经网络的异或问题分类-matlab language BP neural network based on the XOR problem classification
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一个简单的神经网络训练，一个二层的神经网络实现异或的功能-A simple neural network training, a different layer of the neural network function or
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This "classic" style of neural network is used for spontaneously generating an algorithm for the analysis of numeric patterns. The goal is to "teach" the network how to analyze a desired set of numeric inputs. For instance, the network might be taugh
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基于c++实现bp神经网络实现异或功能 有助于了解神经网络-bp neural network xor
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Training Artificial Neural Network.
XOR Problem.
Summation Units, Log-Sigmoid Neurons with Biases.
Input Layer: 2, Hidden Layer: 2, Output Layer: 1 neurons.
Returns mean square error between desired and actual outputs.
Reference Pape
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BP神经网络解决异或问题，在VC6.0下编译通过-BP neural network to solve the XOR problem, compiled by VC6.0
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Neural network Xor example
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基于BP神经网络的非线性分类，及运用其解决异或问题，并对Iris数据进行分类-Nonlinear classification based on BP neural network and the xor problem, and its appplication on the data of Iris.
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