When the minimal eigenvalue of connection weights matrix is greater than the reciprocal of derivation of its neuron activation function, the network will be convergent in parallel update mode.
当网络连接权值矩阵的最小特征值大于激活函数导数的倒数时，网络并行收敛。
When the minimal eigenvalue of connection weights matrix is greater than the reciprocal of derivation of its neuron activation function, the network will be convergent in parallel update mode.
当网络连接权值矩阵的最小特征值大于激活函数导数的倒数时，网络并行收敛。
应用推荐