Packet sampling which was widely used in network monitoring is a good method to upgrade data packet processing capacity.
数据包采样方法是提升数据包处理能力很好的方法，在网络流量监测分析中得到了广泛应用。
The increasing link speed highlights the inefficiencies of the existing packet capturing engine, which is the critical part of network monitoring.
随着网络速度的增加，作为网络监测关键部分的报文捕获引擎暴露出了在性能上的不足。
Propose wavelet packet decomposition frequency-band monitoring method, diagnose typical failures of rolling bearing, and extract eigenvector to prepare follow-up Neural network identification.
提出了基于小波包分解频带能量监测法，对滚动轴承的几种典型故障进行了诊断，并且提取特征向量，为后续的神经网络识别作准备。
应用推荐