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1·The stopping criteria for sifting and boundary effect are studied for Empirical Mode Decomposition(EMD) algorithm.

对经验模式分解算法中的滤波停止条件和端点延拓问题进行了研究。

2·Specifies the percentage of training cases used to calculate the holdout error, which is used as part of the stopping criteria during neural network learning.

指定用于计算？效组错误的培训案例之百分比，以在类神经网路学习期间作为停止准则的一部分。

3·Owing to the disadvantage that traditional stopping criteria expend hardware resource too much, USES the combination of cross entropy criteria and exterior information by way of the stopping criteria.

针对传统停止迭代准则译码耗费硬件资源的不足，提出了利用外部信息结合交叉熵迭代停止准则作为新的迭代停止准则算法。

4·Both stopping criterions are based on the cross-entropy concept (ce), but the new criterion is simpler than ce criteria and can be realized with lower complexity.

这两种迭代终止准则都是基于互熵(CE)的概念，但是后一种比CE准则更简单，具有更低的计算复杂度。