neural activation function

基本解释

Method: Based on dynamic error correction BP artificial neural network with Hyperbolic Tangent function as activation function and the number of hidden node six.
方法：利用动态学习比率BP算法以双曲正切函数为功能函数的非线性时间序列预测方法。
Methods Based on dynamic error correction BP using artificial neural network with Hyperbolic Tangent function as activation function and the number of hidden node six.
方法利用动态学习比率BP算法以双曲正切函数为功能函数的非线性时间序列预测方法。
BP algorithm is often used to correct weights of neural network because number of hidden nodes, studying speed and generation ability of neural network are related to activation function.
以往的BP算法调节神经元网络的权值，其网络的隐层结点数、网络学习快慢程度及网络的泛化能力都与网络的激励函数有关的。