假如是如许的话，下一个应战将是找到无损办法速度适中为啦使才能调整和需求调整彼此得以坚持更亲密的对齐。
If so, the next challenge will be to find non-destructive ways to moderate the pace in order to bring the capacity to adjust and the need for adjustment into closer alignment.
本文提出一种基于自适应预测的无损压缩方法，该方法利用神经网络模型自学习的能力，自适应的调整预测器的预测系数。
In this paper, a lossless compression method, based on adaptive prediction, is presented. This method USES neural network model to modify the prediction weight.
提出了基于FPGA的无损伤切换的实现方案，并重点介绍了实现中采用的相位调整、弹性存储器和自动切换控制等关键技术。
The implementation scheme based on FPGA is proposed, and key techniques such as phase adjusting, elastic store and automatic switch control are introduced.
提出了基于FPGA的无损伤切换的实现方案，并重点介绍了实现中采用的相位调整、弹性存储器和自动切换控制等关键技术。
The implementation scheme based on FPGA is proposed, and key techniques such as phase adjusting, elastic store and automatic switch control are introduced.
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