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: |
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Author:yongweihuang |
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Description: Batch version of the back-propagation algorithm.
％ Given a set of corresponding input-output pairs and an initial network
％ [W1,W2,critvec,iter]=batbp(NetDef,W1,W2,PHI,Y,trparms) trains the
％ network with backpropagation.
％
％ The activation functions must be either linear or tanh. The network
％ architecture is defined by the matrix NetDef consisting of two
％ rows. The first row specifies the hidden layer while the second
％ specifies the output layer.
％-Batch version of the back-propagation algorithm. Given a set of corresponding input-output pairs and an initial network [W1, W2, critvec, iter] = batbp (NetDef, W1, W2, PHI, Y, trparms) trains the network with backpropagation. The activation functions must be either linear or tanh. The network architecture is defined by the matrix NetDef consisting of two rows. The first row specifies the hidden layer while the second specifies the output layer. Platform: |
Size: 2048 |
Author:张镇 |
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Description: 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)，它的网络结构及算法直观、简单，在工业领域中应用较多。-Artificial Neural Networks (Aartificial Neural Network, under the short title of ANN) is a simulation of the structure of biological neurons and the information put forward a method of treatment. At early 1943, by Warren S. Mcculloch psychologists and mathematicians Walth H. Pitts proposed mathematical model of neurons, was left out in the cold for some time, and the rapid rise of the 80' s [1]. ANN because the general concern of the people is the essence of it is because of the non-linear characteristics of parallel processing capabilities, strong robustness and self-organizing capacity of self-learning. Research one of the most sophisticated are the error-propagation model of the algorithm (BP algorithm, Back Propagation), its network structure and algorithm for intuitive, simple, application in the industrial field more. Platform: |
Size: 159744 |
Author:pjh |
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Description: 伺服电机的神经网络参数自整定程序，利用BP误差反向传播算法改变PID 控制参数以获得优越的控制效果-Servo motor parameters of the neural network self-tuning procedures, the use of error back-propagation algorithm BP to change PID control parameters for superior control Platform: |
Size: 1024 |
Author:阿满 |
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Description: 把genetic algorithm加到传统BP算法，对其改进，从而提高收敛速度。-back-propagation algorithm- a modified algorithm to embed GA into BP Platform: |
Size: 2048 |
Author:sean |
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Description: 我们最常用的神经网络就是BP网络，也叫多层前馈网络。BP是back propagation的所写，是反向传播的意思。-We are the most commonly used neural network is a BP network, also known as multi-layer feedforward network. BP is written by the back propagation is the meaning of back-propagation. Platform: |
Size: 1024 |
Author:肖晔 |
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Description: There are three methods (1, 2 & 3 [Back-propagation]) for forecasting a time series. Here is a collection of MATLAB programming, screen shorts, Fig files giving results. Follow comments in the files to run programs Platform: |
Size: 262144 |
Author:tom tom |
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Description: useful for learning the algorithm for extraction of the system when write the code in back propagation int the system-useful for learning the algorithm for extraction of the system when write the code in back propagation int the system Platform: |
Size: 342016 |
Author:surya |
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Description: Matlab的神经网络工具箱实用指南
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 is a practical guide to the first chapter a basic introduction to neural networks, and the second chapter, including designated by the toolbox on network structure and symbols of basic materials and the establishment of neural networks, some of the basic functions, such as new, init, adapt and the train. Chapter III in order to back-propagation network as an example to explain the back-propagation network, the basic process principles and applications. Platform: |
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Author:董志疆 |
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Description: Normalisation Program and Back propagation Neural network program and details of using the program. Platform: |
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Author:Subba |
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Description: a transmission line fault location model which is based on an Elman recurrent network
(ERN) has been presented for balanced and unbalanced short circuit faults. All fault situations with
different inception times are implemented on a 380-kV prototype power system. Wavelet transform
(WT) is used for selecting distinctive features about the faulty signals. The system has the advantages of
utilizing single-end measurements, using both voltage and current signals. ERN is able to determine the
fault location occurred on transmission line rapidly and correctly as an important alternative to standard
feedforward back propagation networks (FFNs) and radial basis functions (RBFs) neural networks. Platform: |
Size: 761856 |
Author:charlie |
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