为提高并行网络模拟的可用性与运行效率，需要研究有效的拓扑划分方法。
To improve the usability and running efficiency of the parallel network simulation, effective topology partitioning method is required.
通过构造一个特殊的多层前向神经网络，利用模拟并行测量装置的基本原理，设计了相应的谐波监测电路。
Using the basic principle of analog parallel harmonics measurement and a special multi-layer feedforward neural network, a corresponding harmonics measurement on-line is built.
神经网络计算机能模拟人脑的并行处理方式，具有惊人的自学习、思维、推理、判断和记忆的功能。
Neutral network computer can simulate human brains in parallel information processing manner, with functions of striking self-learning, thinking, reasoning, judging, and memorizing.
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。
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.
神经网络具有类似人脑的并行处理结构，能够模拟人脑对刺激的反应方式进行工作，可以用于解决磁共振图像分割问题。
With the parallel structure like the human brain, neural networks can simulate the reaction of brain which is stimulated, and can be applied for MRI segmentation.
为提高并行网络蠕虫模拟的性能，需要对蠕虫模拟任务进行合理的划分。
To improve the performance of parallel simulation of network worms, the simulation task of worms should be partitioned reasonably.
神经网络以大规模模拟并行处理为主，具有很强的鲁棒性、容错性和自学能力。
The neural network gives first place to simulating parallel processing in large scale, with strong character of robustness, fault tolerance and studies ability independently.
研究并设计实现了并行机互联网络通信性能模拟系统——SINOMP。
This paper designs a simulation system for interconnection network communication performance of multi-processor named SINOMP.
研究并设计实现了并行机互联网络通信性能模拟系统——SINOMP。
This paper designs a simulation system for interconnection network communication performance of multi-processor named SINOMP.
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