The method based on the cubic B-spline function, beam vibration function (or trigonometric functions) and variation principle.
这个方法是建立在三次样条函数、梁振动函数(或三角函数)及变分原理基础上。
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。
According to existing motions, the algorithm adopts a warping function represented by multi -level B-spline function to generate detailed motion level by level in order to get the goal motion.
该算法根据已有的运动，采用多级B -样条表示的规整函数产生不断细化的运动，从而得到最终的目标运动。
New algorithm need not directly compute values of B-spline interpolatory function, the values were computed using B-spline scaling relation on sampling points, which had simple and uniform coding.
提出的算法不用计算b -样条函数的显式值，而是利用B -样条的尺度关系计算采样点的值，具有一致且简单的编码。
New algorithm need not directly compute values of B-spline interpolatory function, the values were computed using B-spline scaling relation on sampling points, which had simple and uniform coding.
提出的算法不用计算b -样条函数的显式值，而是利用B -样条的尺度关系计算采样点的值，具有一致且简单的编码。
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