Description: 误差反向传播网络(Back propagation network,简称BP网络)是神经网络中最活跃的方法，且绝大多数采用了三层结构(输入层、一个隐含层和输出层).BP网络是一种非线性映射人工神经网络.本程序用vb实现的bp算法-error back-propagation network (Back propagation network, called BP) neural network is the most active, but the majority adopted a three-tier structure (input layer, a hidden layer and output layer). BP network is a non-linear mapping of artificial neural networks. The procedures used vb the algorithm to achieve bp Platform: |
Size: 28672 |
Author:fuyu |
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Description: 完整的反向传播神经网络模式识别C++源代码,原版权威所著,学习物有所值.-integrity of the back-propagation neural network pattern recognition C source code, original authoritative book, learning value for money. Platform: |
Size: 215040 |
Author:John NI |
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Description: neural network,神经网络的BP算法的代码，保证能运行，Back Propagation-neural network, the BP neural network algorithm code, the guarantee of operation, Back Propagation Platform: |
Size: 3072 |
Author:young |
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Description: bp神经网络算法是解决最优化问题的先进算法之一，本论文讨论了神经网络中使用最为广泛的前馈神经网络。其网络权值学习算法中影响最大的就是误差反向传播算法（back-propagation简称BP算法）。BP算法存在局部极小点，收敛速度慢等缺点。基于优化理论的Levenberg-Marquardt算法忽略了二阶项。该文讨论当误差不为零或者不为线性函数即二阶项S(W)不能忽略时的Hesse矩阵的近似计算，进而训练网络。-bp neural network algorithm to solve optimization problems, one of the advanced algorithm, the paper discusses the neural network in the most widely used feed-forward neural network. Its network weights learning algorithm in the greatest impact is the error back-propagation algorithm (back-propagation algorithm referred to as BP). BP algorithm for the existence of local minimum points, such as the shortcomings of slow convergence. Optimization theory based on the Levenberg-Marquardt algorithm ignores the second-order item. In this paper, the discussion when the error is not zero or not that is second-order linear function of S (W) can not be ignored when the Hesse matrix of approximate calculation, and then training the network. Platform: |
Size: 19456 |
Author:刘慧 |
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Description: 每一个训练范例在网络中经过两遍传递计算：一遍向前传播计算，从输入层开始，传递各层并经过处理后，产生一个输出，并得到一个该实际输出和所所需输出之差的差错矢量；一遍向反向传播计算，从输出层至输入层，利用差错矢量对权值进行逐层修改。BP算法有很强的数学基础，戏剧性地扩展了神经网络的使用范围，产生了许多应用成功的实例，对神经网络研究的再次兴起过很大作用。
-Each training example in the network passing through the calculation twice: once to move the spread of computing, from the beginning of input layer, transmission floors and processed to produce an output, and a the actual output and the difference between the desired output error vector again to reverse the spread of computing, from the output layer to the input layer, using error vector values of the right to amend the layers. BP algorithm has a strong mathematical foundation, dramatically expanded the use of neural networks, resulting in a number of successful examples of application of neural network research have a significant role in the rise once again. Platform: |
Size: 1024 |
Author:军军 |
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Description: 基于matlab的新型信号处理算法集。包括模拟退火、遗传算法、反向传播神经网络、小波变换等等，对于统计信号处理很有参考价值。-Matlab based on a new type of signal processing algorithms. Including simulated annealing, genetic algorithm, back-propagation neural network, wavelet transform, etc., for statistical signal processing useful reference value. Platform: |
Size: 4231168 |
Author:caruchi |
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Description: 這是一個類神經網路中倒傳遞類神經網路，應用於圖形識別上，可以把兩個不同分類的點，藉由BP找出他的分割線進行區分-This is a type of neural network back-propagation neural network applied to pattern recognition, it can be classified into two different points, by BP to find his distinction between partition lines Platform: |
Size: 2048 |
Author:flower |
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Description: This program simulates a 3 or 4-layer Neural Network, and can be used to
simulate an arbitrary, complex, or non-linear function that would be
difficult to implement by traditional methods. The Back Propagation
method is used "teach" the network the desired function.
Adjacent layers of the net are fully interconnected that is, every
neuron in layer 1 is connected to every neuron in layer 2, and every
neuron in layer 2 is connected to every neuron in layer 3 (1->2, 2->3).
With a 4-layer net, there is further interconnection: 1->2, 1->3, 2->3,
2->4, 3->4.
- This program simulates a 3 or 4-layer Neural Network, and can be used to
simulate an arbitrary, complex, or non-linear function that would be
difficult to implement by traditional methods. The Back Propagation
method is used "teach" the network the desired function.
Adjacent layers of the net are fully interconnected that is, every
neuron in layer 1 is connected to every neuron in layer 2, and every
neuron in layer 2 is connected to every neuron in layer 3 (1->2, 2->3).
With a 4-layer net, there is further interconnection: 1->2, 1->3, 2->3,
2->4, 3->4.
Platform: |
Size: 49152 |
Author:cso |
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Description: Back-Propagation Neural Network Model for predicting the traffic situation of Australia. -This procedure aims to solve the prediction of the Australia Highway traffic situation. Platform: |
Size: 10240 |
Author:Justin Han |
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