We proposed an extension of Akaike's relative power contribution that could be applied to data with correlations between noises. This method decomposes the power spectrum into a contribution of the terms caused by correlation between two noises, in addition to the contributions of the independent noises. Numerical examples confirm that some of the correlated noise has the effect of reducing the power spectrum.

翻译：我们提出了对Akaike相对功率贡献的扩展，可应用于存在噪声间相关性的数据。该方法将功率谱分解为独立噪声贡献与两个噪声间相关性导致的项贡献两部分。数值实例证实，部分相关噪声具有降低功率谱的效果。