合并研究结果的统计学方法通常采用待估效应测量值的方差的倒数来对每一个研究的影响进行加权。

Statistical methods for combining the results of studies generally weight the influence of each study by the inverse of the variance for the estimated measure of effect.

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本文将广义最小方差策略与极点配置策略相结合并采用正则化及相对死区技术提出了一种鲁棒自校正显式算法，并给出了鲁棒性分析，物理实验结果和仿真结果。

A self-tuning robust explicit algorithm with normalization and dead-zone is presented combining generalized minimum variance with pole-placement strategy , with the robustness discussed.

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