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这是cmu大学的一个研究小组编写的神经网络中反向传播算法的源代码，很有参考价值。-This is a university research group to prepare the neural network back-propagation algorithm source code of great reference value.
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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。
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Backpropagation Network Time-Series Forecasting 源码, 经典的BPN人工神经网络例子源码-Backpropagation Network Time-Series Forecasting source, the classic example of artificial neural network BPN source
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人工神经网络vbp算法 人工神经网络电子讲稿-Artificial neural network artificial neural network algorithm vbp electronic scr ipt
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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.
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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
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人工神经网络(Aartificial Neural Network，下简称ANN)是模拟生物神经元的结构而提出的一种信息处理方法。早在1943年，已由心理学家Warren S.Mcculloch和数学家Walth H.Pitts提出神经元数学模型，后被冷落了一段时间，80年代又迅猛兴起［1］。ANN之所以受到人们的普遍关注，是由于它具有本质的非线形特征、并行处理能力、强鲁棒性以及自组织自学习的能力。其中研究得最为成熟的是误差的反传模型算法(BP算法，Back Propagation)，它的网络
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双隐层反向传播神经网络例程，教学用，算法解释清晰-Two-hidden layer back-propagation neural network routines, teaching the algorithm explained clearly
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類神經網路之倒傳遞神經網路模型，使用matlab之c語言編輯-Artificial Neural Network- Back Propagation code with Matlab
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BP neural network implementation with generalized delta learning rule and momentum-BP neural network in Matlab
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Neural network descr iption.
a sample fo back-propagation neural network
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Matlab编写的BP误差反向传播神经网络算法-Matlab BP prepared by back propagation neural network algorithm
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back propagation (neural network)
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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.
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Abstract-This paper introduces the new concept of Artificial
Neural Networks (ANNs) in estimating speed and
controlling the separately excited DC motor. The neural
control scheme consists of two parts. One is the neural
estimator, which is us
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遗传算法优化神经网络黑箱函数通用MATLAB源码，仅供学习参考。-Genetic algorithm neural network black-box function universal MATLAB source code, study reference purposes only.
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用一个多层前向神经网络，采用反向传播算法依据控制要求实时输出Kp、Ki、Kd，依次作为PID控制器的实时参数，代替传统PID参数靠经验的人工整定和工程整定，以达到对大迟延主气温系统的良好控制。-We use a multilayer feedforward neural network using back propagation algorithm and based on control requirements.This net can real-time output Kp, Ki, K
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神经网络原理 Simon Haykin 英文版
基本涵盖了神经网络的许多基础部分和重要方面。像Back Propagation， Radial-Basis Function，Self-Organizing Maps，以及single neuron中的Hebbian Learning, Competitive Learning和LMS Learning。 -Neural network theory Simon Haykin in English covering the neural net
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BP神经网路的matlab仿真，该程序用matlab演示了BP神经网络的学习机制。-simulation of Back Propagation neural network
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倒傳遞類神經網路,廣泛應用於人工智慧系統-Neural backpropagation is the phenomenon in which the action potential of a neuron creates a voltage spike both at the end of the axon (normal propagation) and back through to the dendritic arbor or dendrites, from which much of
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