In respect of eliminating error caused by time delay and making reasonable prediction to the data stream, many methods are experimented in order to realize the aim of real time tracking.
在消除时间上的延迟所造成的误差以及对这些数据流进行合理的预测等方面，采用了多种解决方案，以达到实时跟踪的目的。
This paper proposed a new prediction method for outliers over data stream based on sparse representation to improve the optimum prediction speed and performance of outliers over data stream.
为了提高数据流中异常数据的预测速度与精度，提出一种基于稀疏表示的数据流异常数据预测方法。
During an encoding mode, a stream of data blocks is received and at least one motion vector and one motion compensation prediction value for each macro-block are generated.
在编码模式期间，接收数据块流并为每个宏块产生(12)至少一个运动矢量和至少一个运动补偿预测值。
During an encoding mode, a stream of data blocks is received and at least one motion vector and one motion compensation prediction value for each macro-block are generated.
在编码模式期间，接收数据块流并为每个宏块产生(12)至少一个运动矢量和至少一个运动补偿预测值。
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