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: 反向传播算法也称BP算法。由于这种算法在本质上是一种神经网络学习的数学模型，所以，有时也称为BP模型。-Back-propagation algorithm, also known as BP algorithm. As a result of this algorithm is essentially a neural network to learn the mathematical model, therefore, sometimes referred to as BP model. Platform: |
Size: 29696 |
Author:yongweihuang |
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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: 反向传播算法也称BP算法，是一种神经网络学习的数学模型，解决多层前向神经网络的权系数优化-Back-propagation algorithm, also known as BP algorithm is a neural network study of the mathematical model and solve multi-layer feedforward neural network weights optimization Platform: |
Size: 3402752 |
Author:wangzhuz |
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Description: matlab神经网络工具箱的实用指南，第一章是神经网络的基本介绍，第二章包括了由工具箱指定的有关网络结构和符号的基本材料以及建立神经网络的一些基本函数，例如new、init、adapt和train。第三章以反向传播网络为例讲解了反向传播网络的原理和应用的基本过程。-matlab neural network toolbox of the Practical Guide, chap neural network are the basic introduction, chapter II, including designated by the toolbox on the network structure and symbols of the basic materials, as well as neural network set up some basic functions, such as new, init, adapt and train. Chapter III in order to reverse the spread of the network as an example to explain the back-propagation networks, the basic principle and application process. Platform: |
Size: 84992 |
Author:sanjinzhi |
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Description: This program is to one-step EEG prediction. it is done by a fuzzy neural network based on a chaotic back propagation training method. Platform: |
Size: 6144 |
Author:Mehran Ahmadlou |
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Description: This program is prepared as an one-step EEG predictor. this is used a fuzzy neural network which is trained by a chaotic back propagation method Platform: |
Size: 197632 |
Author:Mehran Ahmadlou |
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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: 使用bp（反向传播算法）实现分类问题，并观察分类过程中误差的变化。-Use bp (back-propagation algorithm) to achieve the classification and observe the changes in classification process in the error. Platform: |
Size: 30720 |
Author:王晶 |
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Search - back propagation