The conditional average is a technique to extract a typical waveform from bursty or quasi-periodic phenomena regarded as a combination of deterministic trend and residual fluctuations (or probabilistic part). The article proposes a new conditional average technique that is an extension from what is called the template method that allows automatic selection, using the correlation analysis, of the identical events of the phenomena. The proposed method is applied on a quasi-periodic oscillation observed in a linear magnetized plasma, and successfully divides the phenomenon into the deterministic trend and residual fluctuations. Moreover, the statistical error analysis on the power of the residual fluctuations discloses the presence of mutual interactions between the deterministic trend and the residual fluctuations.
条件平均是一种从突发性或准周期性现象中提取典型波形的技术，该现象被视为确定性趋势与残余波动（或概率部分）的组合。本文提出了一种新的条件平均技术，它是所谓模板方法的扩展，该方法利用相关分析自动选择现象的相同事件。所提出的方法被应用于线性磁化等离子体中观测到的准周期振荡，并成功地将该现象分解为确定性趋势和残余波动。此外，对残余波动功率的统计误差分析揭示了确定性趋势与残余波动之间相互作用的存在。