We use a parallel and with feedback fusion system architecture, cascade D-S evidence theory to be fusion algorithm. Finally, a graphic target recognition system is realized.
系统采用有反馈的全并行融合系统结构，以分级式d S证据推理为数据融合算法，最终实现一个图形化的目标识别系统。
This paper presents a parallel sorting algorithm based on neural network derived from the harmony theory neural network.
文中从和谐理论神经网络派生一种新的神经网络模型，并以该模型为基础提出了一种新的并行分类算法。
In this paper, we extend the idea of DEDS (Discrete Event Dynamie System) theory and present a fast parallel algorithm for communication network random simulation.
引入现代控制科学离散事件动态系统摄动分析思想，提出通信网络随机模拟的快速并行算法。
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