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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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有限脉冲神经网络MATLAB源码，由波兰国立大学生物医药信号处理实验室提供。FIR 神经网络属于一种BP神经网络。-Finite Impulse Response (FIR) neural network models each synapse as a linear filter to provide dynamic interconnectivity. Temporal backpropagation is used to train the network in which error t
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一个前馈反向传播人工神经网络的实现，并应用CUDA加速-Implementation of a feed-forward backpropagation artificial neural network using CUDA
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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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神经网络，前向传播，反向传播，减小loss值(Neural network, forward propagation, backpropagation, reduce loss value)
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利用BP神经网络对邮件分类，2分类，实现反向传播算法细节，非直接函数调用(BP neural network is used to classify mail, 2 classifications, to implement the details of backpropagation algorithm, non direct function call.)
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深度学习代码CNN，用VC++ 实现，很有参考价值，神经网络权值参数反向传播实现。(Deep learning code CNN, implemented with VC++, is of great reference value, and neural network weight parameter backpropagation is realized.)
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