The BP neural network was proved to be an excellent parallel data-handling method with dark-box operating performance, powerful studying and generalizing ability.
BP神经网络是一个优秀的并行数据处理方法，具有暗箱操作性、以及强大的学习能力和推广能力。
A general forward displacement solution for parallel robot based on self-configuration quick BP neural network is presented, and analysis result for the engraving robot is given.
给出了基于自构型快速BP网络的并联机器人位置正解通用方法并以雕刻机器人为例进行了分析。
This algorithm can resolve the interference among attributes with different data types, and decrease the size of BP neural network, and realize the parallel computation of attributes matching.
该算法能有效地消除不一致信息的干扰，降低神经网络的规模，并且可以实现不同数据类型的属性集之间属性匹配过程的并行计算。
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