并针对一个实际的网络时延测量结果进行了分析，验证了该算法的有效性。
Finally, the algorithm proves effective by analyzing an actual network delay measurement result.
该文根据优化目标推导了时钟同步优化算法，从而提高单向网络时延测量的精确性。
And the clock synchronization optimization algorithm which improves the accuracy of one-way network delay measurement is deduced based on the optimizing goal.
还利用三种飞机缩比模型的暗室测量数据，研究了时延神经网络分类器中时延单元数目对分类精度的影响以及分类器的分类性能。
The effect of time delay unit number on classification precision and the performance of TDNN classifier using three typical aircraft dark room data measured with scale model were studied.
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