orthogonal function basis

基本解释

In the process of application of Improved BP algorithm in PNN, the input functions and the network weight functions are represented as expansion of a same orthogonal function basis.
在改进BP算法与网络训练的结合过程中，权函数及输入函数皆被用同一正交基函数展开。
In consideration of the complexity of the aggregation operation of time in process neural networks, a new learning algorithm based on function orthogonal basis expansion is proposed.
该文在考虑过程神经网络对时间聚合运算的复杂性的基础上，提出了一种基于函数正交基展开的学习算法。
And the complex variable moving least-square approximation based on the orthogonal basis function is discussed in detail.
提出了复变量移动最小二乘法，并详细讨论了基于正交基函数的复变量移动最小二乘法。