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模式识别课程作业-神经网络分类IRIS数据集.共两层网络，程序有详细注释。程序结果将输出到EXCEL文件中，也很详细。-Course work in pattern recognition- Neural Network Classification IRIS data set. A total of two networks, a detailed program notes. Program results will be output to the EXCEL file, and very
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back probagation in neural network
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BP-神经网络 The neural network is trained with the Levenberg-Marquardt algorithm.
The activation functions can be either linear ( L ) or hyperbolic tangent ( H ).-Backpropagation neural network with one hidden layer for multivariate calibration. (Desig
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backpropagation for Neural network
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MATLAB neural network backprop code
This code implements the basic backpropagation of
error learning algorithm. The network has tanh hidden
neurons and a linear output neuron.
adjust the learning rate with the slider
-MATL
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BP神经网络训练程序，基于梯度学习算法，对非线性函数（hermitian）逼近。-The BP neural network training program，which is based on the steepest descent Method，，，backpropagation network (BP) approximation of the nonlinear function。
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This a sample of a simple image classification using K-Nearest Neighbor and Backpropagation Neural Network. It uses block averaging in feature extraction process.-This is a sample of a simple image classification using K-Nearest Neighbor and Backprop
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this simple implementation of forecasting using neural network backpropagation-this is simple implementation of forecasting using neural network backpropagation
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Backpropagation, an abbreviation for backward propagation of errors , is a common method of training artificial neural networks used in conjunction with an optimization method such as gradient descent. The method calculates the gradient of a loss fun
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Tran a neural network using a combination of PSO and backpropagation algorithm
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是一种按误差逆传播算法训练的多层前馈网络，是目前应用最广泛的神经网络模型之一。BP网络能学习和存贮大量的输入-输出模式映射关系，而无需事前揭示描述这种映射关系的数学方程。(It is a multilayer feedforward network trained by error backpropagation algorithm, and is one of the most widely used neural network models. BP networks can learn a
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