To counter the complexity and limitation of traditional digital distinguish methods, Script Digital Distinguish System based on BP Neural Network is proposed.
针对传统的数字识别方法的复杂性和局限性，提出了基于BP神经网络的手写体数字识别系统。
Considering the complexity and the time variability of industrial process, an adaptive Supervised Distributed Neural Networks (SDNN) is proposed for modeling of industrial process.
针对工业生产过程的复杂性和时变性，提出一种用于工业生产过程建模的自适应监督式分布神经网络(SDNN)。
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。
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