In this paper, a nonparametric estimator terminated of failure rate is constructed based on censored data, and its rates of convergence in mean square and strong consistency are given respectively.

本文在截尾样本下构造了失效率的一种截尾非参数估计，并给出了其均方收敛及强相合性的局部一致收敛速度。

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On the other hand, we also give several terse sufficiency conditions where the fuzzy mean convergence of (G) fuzzy integrals implies the convergence in fuzzy measure and making them equivalent.

另一方面，文中还给出了广义模糊积分平均收敛蕴涵依测度收敛的几个简洁的充分性条件，以及使两者等价的条件。

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In comparison with traditional LMS algorithm, WO-LMS algorithm can achieve both lower steady mean square error and faster convergence speed.

与传统的LMS算法相比，WO - LMS算法既提高了收敛速度又可以得到较低的稳态均方误差。

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