deleting hidden neuron 隐单元删除
one hidden layer neuron 单隐层神经元
neuron in hidden layer 隐含层神经元
adaptive hidden layer neuron algorithm 隐层神经元自适应算法
By using the astringency of error criteria function, the number of hidden neurons can be decided reasonably, according to the distribution of signal phase difference between the antenna array, the representative hidden neuron centers can be selected.
利用误差准则函数的收敛性，合理确定模型的隐层神经元数目，根据阵列信号相位差特征的空间分布特点，选择具有代表性的隐层神经元的中心，构建的RBF神经网络更能反映阵列的测向能力。
参考来源 - 一种改进的RBF神经网络DOA估计方法·2,447,543篇论文数据，部分数据来源于NoteExpress
Besides, its simple and regular topology make it easy to synthesize the neural networks, especially for the hidden neuron, and suitable for the optical implementation.
另外，洗牌型全互连神经网络整齐、简单的结构方便了网络的综合，特别是网络隐单元的综合，并且十分适合于神经网络的光学实现。
The principle and methods to determine the network parameters such as number of neuron in hidden layer, excitation function and the convergence accuracy have been analyzed in detail.
并且详细叙述了神经网络结构参数如隐含层神经元个数、激励函数、网络收敛精度等的确定原则和方法。
In this scheme, the inputs of hidden layer neurons are acquired by using the gradient descent method, and the weights and threshold of each neuron are trained using the linear least square method.
在该方案中，通过梯度法获取隐层神经元的输入，使用线性最小二乘法训练各神经元的权值和阈值。
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