A new recurrent neural network based on B-spline function approximation is presented. The network can be easily trained and its training converges more quickly.
提出一种新的基于基本样条逼近的循环神经网络，该网络易于训练且收敛速度快。
The meshing stiffness is calculated by employing 3-dimensional FEM and its function is formed by cubic spline interpolation and approximation of the discrete mesh points in a mesh period.
采用三维有限元法计算了斜齿轮副啮合刚度，用三次样条插值拟合得到时变啮合刚度函数。
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